..
ICES
C.M. 1986/C:8
Ref. Biological Oceanography
Cttee., Sess. Q
ANNUAL CYCLES AND PHENOMENA ON OTHER TIME SCALES
IN TEMPERATURE, SALINITY, NUTRIENTS AND PHYTOPLANKTON
AT HELGOLANJ REEDE 1962 - 1984
I'
..
by
•
G. Ra1Qch ; J. Berg,
Institut für Meereskunde der Universität Hamburg,
Troplowitzstr. 7, 2000 Ha~burg 54
and
•
E. Hagmei er,
Biologische Anstalt Helgoland,
Meeresstation Helgoland, 2192 Helgoland
ABSTRACT
The long-term time series of' temperature, salinity, plant
nutrients and phytoplankton biomass at Helgoland Reede in the
German Bight are investigated with respect to prominent time
scales by spectral analysis of variance. This analysis was based
on 23 years of data from 1962 to 1984.
•
,
I
The data are presented in the form of annual cycles by projecting
the data into one year, to demonstrate the dominant features of
the annual dynamics. It turns out that the cycles of diatoms and
silicate are inversely related to each other, more than are
diatoms and phosphate. The annual cycles of the nutrients nitrate
and nitrite are inversely related to the flagellates# biomass.
The Elbe river outflow, which is directly related to the nitrogen
compounds, seems to prepare the situation for relatively hig1
flagellates# biomass development during summer after diatoms,
decrease due to the depleted silicate. Thus silicate seems to
limit the diatoms# development in early sum~er at Helgoland, but
not phosphate or nitrate, and later on flagellates take over the
leading role.
Changing to the frequency domain, it turns out that the outstanding frequency in many of the spectra is the annual frequency. There most of the variance is found for the parameters sea
surface temperature, phosphate, and nitrate. Salinity, nitrite,
ammonia, silicate; the phytoplankton entities, and Elbe river
discharge exhibit the bulk of their total variance in the frequency band 1 <f<10 cycles/year.
For phosphate, nitrate, and
nitrite the spectrum shows constant (or even decreasing) variance
for frequencies smaller than 1/year, while the variance decreases, similar to temperatur~, for frequencies larger' than
1/year. Most of the parameters depend on frequency with a decay
rate of about -5/3 for frequencies > 10 cycles/year. Nitrate and
. silicate exhibit a stronger decay with a rate of about -2.12,
Elbe river discharge with a rate of -3.43. In the frequency band
1
,1 "f < 10 cycles/year most decay rates. are weaker than -5/3
, (except for phosphate and nitrate), between -0.5 (for diatoms)
.and-1.5.
,
; 1. Introduct ion
· The Helgoland Reede time series are amongst the longest and most
· complex chemical and biological data sets on the European
,continental shelf. The time series were started in 1962 by the
Biologische Anstalt Helgoland and include aperiod of rising
: human impact on North Sea coastal waters.
· The Helgoland data set provides a unique possibility to ,investi· gate, on which time scales the essential processes within the
'coastal marine plankton system take place. Due to.the lack of
· sufficiently long time series, only very few investigations exist
: about time scales in chemical and biological data sets andif,
they usually refer only to very few state variables (e.g. TONT &
: PLATT, 1978).
· As is known, in an isotropie turbulence field the spectrum
: decreases exponentially with wave number by a decay rate of -5/3.
The first one applying. this theoretical result to the
interpretation of chlorophyll variance spectra was PLATT (1972),
· for time scales of hours. Since then many authors obtained wave
: number. spectra for, chlorophyll measurements on the basis of
: spatial sections. Statements about the spectral distribution of
: spatial variance have sometimes been transferred to time by
assuming the validity of the "frozen field " hypothesis (OKUBO,
1980; PLATT &DENMANN, 1975). Results for time seal es larger than
: 1 day are hardly given (e.g; TONT &PLATT, 1978).
I
1
The Helgoland.data set allows for direct investigation of time
• scales in the range of, say, 5 days to 23 years. Long-term trends
: occurring on time scales from 2 to 23 years have been already
: presented and discussed by BERG &RADACH (1985), RADACH & BERG
(1986), and GILLBRICHT (1986). Here we discuss mainly events and
variances on the various shorter time scales in more detail.
, It is undecided whether. an exponential decrease of variance with
: a decay.ra~eof -5/3 should be expected for the frequency ranges
and location investigated here~ In any case, it is striking that
· manyof the parameters exhibit a decay of variance with a rate of
, about -5/3 for frequencies larger than 10 cycles/year.
2. Material and methods
, Surface samples between Helgoland main island and the "Düne" (54
; 11.3-N, ,7 54.0-E)) have been collected since 1962, first on
: three days, later on five days per week. After, temperature
measuiement, samples were analysed for salinity and the nutrients
,phosphate, nitrate, nitrite, ammonium, and silicate; Phytoplank0
0
, ton stock was estimated by the technique,of,UTERMöHL (1958).Con-
: versions to carbon follow STRATHMANN (1967). Phytoplankton is
subdivided into diatoms and the rest, maily consisting of flagellates.
Details of the data of single years can be takenfrom the
annual reports of the BIOLOGISCHE ANSTALT HELGOLAND (1962-1984);
2
•
3. Annual cycles
Todemonstrate the importance of the annual period compared to
smaller periods t all 23 years of data are plotted into one year
(Figs. 1a-12a). In Figs. 1b to 12b the mean annual cycles are
presented t together with a confidence band of a width of two
standard deviations. Thus the mean value for. every day lies within this band with an error probabilityofmuch less than 0.1 %.
In the following the term "var iability" always means absolute
variabil ity.
•
Water temperatures and salinities off Helgoland are strongly influenced by wind t moving and mixing of water masses of. different
origin t and, bY. river runoff, precipitation t .and heat flux
(BECKER; 1981)~ In winter time; occasionally drift ice is transported from coastal areas as far as Helgoland. Surface temperatures (Fig.1) follow adefinite, annual cycle. Summer maxima are
reaching 16 to 20 ·C. Variability in summer is lessthan in winter timet where minima are mostly higher or lower thän the calculated mean values~ Surface salinity (Fig.2) has also a typical
mean course during a year t .but large deviations from mean values
occur. In general, salinities in March and May are higher and in
April lower than published for the period 1965-1975 (WEIGEL,
1978). Much of the variations may originate ih different meteorological forcing t causing the water with important freshwater
ädmixtures to touch Helgoland or to flow northward along the
Wadden Sea.
To judge the situation at Helgoland it is important to consider
the discharge of the Elbe river (Fig. 3), as an indicator
describing the continental, run off. The annual cycle iS,dominated
by isolated discharge everits~ The meari cycle represents only a
paar impression ofthe dynami~ of discharge. It has its maximum
in April, .its minimum in August. Variability has its maximum in
January, its minimum in October. In summer strang discharge
events occur. very rarely. It is reasonable tocompare the
discharge of the Elbe river with surface salinity near Helgoland t
and indeed, for time scales larger than two years a clear inverse
relation can be established (BERG &RADACH, 1985).
The amount of nutrients in solution is the result of supplies by
rivers and remineralization;arid reduction by primary production
and currents leaving the area~ The different nutrients exhibit
different annual cycles.
.
The concentration of phosphate (Fig~ 4) is nearly co~stant from
October, till the end of March. Its decline in April and May is
reflecting the uptake by multiplying diatoms. Comparing phosphate
consumption .with phytoplankton stock (Fi~.10) we see,hard]y.. anY
relation (see also GILLBRICHT, 1986). TO,explain this we must be
aware of the fact that production and not standing stock is the
correct quantity to compare with phosphate decrease; Thus we can
assume e.gj a high grazing pressure on the algae !
This state of low concentrations (0.25 m mol P/m 3 ) remains. unchanged until,July. "Then phosphate increases again., Variability
is strongest during late summer and early Jall, while it is smallest during .the phase of depletion in May/June~ In times of
rising phosphate contents in the water (beginning in July),
3
: excretion and decomposition of organic matter and reminerali: zation are providing more phosphate than the algae are able to
, consume.
: The annual cycle of,nitrate (Fig. 5) has its peak values in
January/February and in May, with a relative minimum in March.'
The high level of.about 25 units decreases from May,to July down
· to less than 5 units. The concentration stays at this level until
October. Then the concentration increases again until January to
: the winter level. Variability decreases steadily from January to
September (excluding April), and it increases again in the same
: steady way to the winterly range ofvariabil ity~ The high values
,of nitrate in winter and spring seem tO,have a direct relation to
: the Elbe river, discharge. : Similar restilts were obtained earlier
, by LUCHT & GILLBRICHT (1978).
· Nitrate distribution indicates more 1nfltience of river input than
phosphate content. This can explain why the effect,of the phyto: plankton spring bloom,is registered, later than in the phosphate
curve. Recovery of nitrate in solution ,is rather slow; partly
: because excreted nitrogen-compounds .will be reused before
: oxydation, partly because remineralization is passing more steps
, and needs a longer time than that of phosphorus~
The annual cycle of nitrite (Fig. 6) has its highest values in
December/January. From January,on nitrite decreases until March,
. has a local maximum in April/May, and then decreases again
'strongly until June. It remains.on this level until September and
· increases. lateron steadily to the level of January. Variability
: is in, winter about 5 times as large as ,in, summer. Nitrite is
:recorded in amounts one order of magnitude lower than nitrate.
Nitrate and ,nitrite have 1ndeed different annual cycles: The
,phase of depletion , is for :nitrite about one month earlier than
,for nitrate. Thehigh ~alues of nitrite in winter and early
spring coincidewith high values of the Elbe discharge. This may
: indicate slow processes of oxydatiori to nitrate in cold water~
Ammonia (Fig. 7) is another transitional nitrogen compound;
,excreted by animals; taken' up by plants and oxydiied by bacteria.
There is no definite annual cycle, deviations from a meari value
:around ,7.5 m mol/m~ are rather large. A predominance of
:degradation inthis time,of thc year should result in slightly
'higher values during fall~'The data seem to back this.
,Total" inorganic nutrient-N maps essentia.lly, the annual cycleof
:nitrate, after adding the fairly constant background of ammonia
'of about 7~5 m mol N/m 3 (Fig;8)~
:For ,silicate (Fig. ,9) the annual cycie starts. 1nwinter and in
,earlY,spring (until April) with the highest concentrations.
Silicate content drops, distinctly "dudng, April arid May;
:corresponding to the spring diatom bloom. However, as with the
,uptake, of phosphate, a quantitative connectionto the standing
'stock,of phytoplankton cannot be.established. The silicate con:sumption, ,as that of phosphate. in spring~ is ten times more than
:expeCted fro~ the amount o( plankton counted; ,Although sma 11
:flagellatesneeding phosphate can be destroyed by fixation or
:concealed by detritus, it seems impossible to overlook a large
4
•
number of silicate containing diatoms. Consequently consumption
and replenishment of phytoplankton should be much quicker than
expected.
The low concentratioris are observed until September. Then, the
concentration increases again to winter values., Obviously there
is averystrong variability in winter (about 4 times that 'of
summer). The high values in winter coincide with high amounts of
discharge of the Elbe river.
•
~
Phytoplankton stocks (Fig. 10), presented by their carbon content, appear tri dev~lop ih .lhe ~classical" form for our latitude
with, two maxima in April/May and August, but this picture is
really formed by the superposition of many short-termed bloom
events. ,While diatoms,are dominating during the spring.maximum,
in summer time large stocks of flagellates are of equal importance.The standing stock in winter is about one to twoorders of
magnitudes smaller than the standing stock in spring and summer;
Variability is - on a logarithmic scale,-fairly const~nt, of
about orie order of magnitude (i.e. the factor of 10).
Diatoms (Fig., 11) appear in several maxima between April. and
September, with contributions of different species, . ~hose
abundance is partly predictable by their demands for light and
temperature; Variability is least in winter, (one ,order of
magnitude) arid greatest ih summer (about two orders of magnitude).
Flagellates (Fig. 12) occur with small, naked forms in iarge
numbers but with low carbon contents all the year round.
Additionally, numerous dinoflagellates can be observed in summertime •. From fall to spring a biomass. of20 - 30 mg C/m 3 ,is not
exceeded. Carbon values during blooms of Ceratia reach 1000 mg
C/m 3 !
To summarize, the annual cycles of diatoms and silicate seem to
be inversely related. The same is true for diatoms arid phosphate.
Nutrients-N of nitrate and nitrite are inversely related to
flagellates- biomass, Elbe discharge andnitrate/ nitrite run
parallelly. Therefore, the nutrient input of N-components by the
river discharge reaching Helgoland prepares the basis for the
Diatoms are not
build-up of flagellates- biomass in summer.
äbl~ to fullyuse the nitrogen load of the water. It is in June~
when blooms of flagellates first.occur, that nitrate and nitrite
fall ,off tO.the lowest levels. ,At this time silicate; which is
vital for diatoms but not for flagellates, has decreasedalready
to very low values. Thus it seems that silicate represerits the
limiting factorfor diatoms, but not phosphate.ornitrate. As the
diatoms make only limited use of ,theplentiful phosphate and Nnutrients, flagellates take over th~ leading role and form the
dominant amount of biomass;
4. Sp'ectral :'analysis
Although there are several gaps of varying lengths in the series,
the
material
is principally suited to investigate
time
scales
from several days to 23 years. After interpolation we performed
spectral
~nalysis
on the full time series.
5
.
; Because we were interested in an as high resolution of the 10wfrequency ~art ofthe variance spectra ~s possib1e; we tried to
, avoid any 10ss of. data. Therefore the Fast-F6urier-Transform ~ith
the necessity of N being apower of 2 cou1d,not be used. For the
same reason; the usua1 technique of partitioning the series ,for
• getting a smoothed spectrum was not app1ied~ We didspectra1
'analysis with a real Fourier transform after prime fact6r sp1iti ting.
:The dots in the figures of the variance spectra represent means
'of five (separated) variance va1ues. The unit 6f variance is the
; square of the unH of the parameter in question. The confidence
interval ,(JENKINS & WATTS, , 1968) of the chi-square distributed
mean variances for now 10 degrees of freedom,is plotted for an
'error probability, of 5% in the lower 1eft edge of the,figures.
:Because ofthe logarithmic sca1e, this interval is valid for all
points of the spectrum.
The variance represented 6y certain frequency ranges' were
:obtained by summing up the variance va1ues in the original
'!spectra (not shown)within.these ranges (Parieva1s theorem). The
:regression 1ines in the figures were ca1cu1ated as least square
fits in the double 10garithmic sca1es a10ng
1n(variance)
, ,
.. ,
=
' ... '
a * 1n(frequency) +
"I
In the spectra of sa1inity;
,frequency of 14.7 days (i.e~
,showing up. This frequency
:region, where the M2-tide is
6.
nitrate, and nitrite thea1iasing
24.7 cyc1es/year) is significant1y
is the resu1t of daily samp1ing in a
of greatest importance~
,5. Interpretation of spectra
From t~e specira we ~an,le~rn, on w~ich sca1e~ the ~iffer~nt processes - physica1, chemieal; or bio10gica1 - mayact and dominate
the deve10pment of chemica1 and bio1ogica1 parameters in the sea.
Here spectra were ca1cu1ated for the time,series of, temperature,
sa1initY,.nutrients and phytoplankton (Figs. 13-24). The spectra
exhibit different.structures. The.outstanding frequency in many
of the spectra is the annua1,frequency, which is demonstrated by
the ca1cu1ation ,of the pcirtions,of variance is percentagesof
total variance of the spectrum within different frequency bands
(Tab.1)~
,
,
I '
I
I '
The variance of temperature (F1g., 13) at He1go1and is near1y exc1usive1y found in the anriua1 period, ~hich cou1d mean that the
annua1 heating cyc1e dominates all other processes 1ike advection
of water masses with different temperaturesand fresh water inf10w. In c6ntrast, variance of sa1inity (Fig. 14) is determined
to 21% by the annu~l ~yc1e; arid 34% of,the total .variance is
found in the range on 1 to 10 cyc1es / Year. Long~term processes
are even more important (25%) than the annual frequency. ,This is
very similar to what the variances of Elbe river dischargeteach
(Fig. 15). 36% of variance is due to periods,either1onger ,or
periods shorter than the annual ~eriod, suggesting that salinity
may be determined by river runoff. In the range of shorter time
scales than 0.1 year salinity shows 18%, but river discharge on1y
5% of variance" demonstrating that discharge events are not hap~
pening on such short scales. Thus salinity must be determined
6
by different processes on these scales.
The aliasing frequency (24.7 cycles/year) is significant in the
salinity spectrum (see also BECKER &KOHNKE, 1978), but not in
the temperature spectrum. This would occur, if e.g. temperature
would be predominantly determined by the heating processes,
acting on larger spatial scales than the processes regulating
salinity, which are mainly connected to the river inflow.
•
Phosphate (Fig. 16) and nitrate (Fig. 17) contain 52% and 41% of
their variance in the annual period, whereas nitrite (Fig. 18),
ammonia (Fig. 19), and silicate (Fi~. 20) have more than 35% of
their variance in the range of 1 to 10 cycles/ year. Phosphate is
hardly determined by processes on long time scales (8%), in
contrast to nitrate (20%). Ammonia (Fig. 19), as an exception,
has nearly no contribution of the annual frequency to total
variance, and 61% of its variance is determined by processes on
time scales less than 1 year. Long-term contributions to variance
are small for nitrite (16%) and silicate (13%) •
The bulk of variance in the plankton series (Figs. 22 - 24) is
contained in the frequency band between 1 and 10 cycles/year and,
for diatoms only, in the higher frequencies (37%). Flagellates
(Fig. 24) behave very different from diatoms (Fig. 23): the
former contain only 2% of total variance in the annual frequency,
66% in the range from 1 to 10 cycles/ year, and only 9% on
shorter scales, whereas diatoms exhibit nearly the same part of
variance in the two higher frequency ranges (36% and 37%) and
only 11 and 16 % in the frequency ranges larger than or equal to
one year. Thus we must assume that the variance spectra of
diatoms and of flagellates must be based on different dynamics.
parameter
variance in % of total variance in the
different frequency bands
f<1
•
sea surface
temperature
salinity
phosphate
nitrate
nitrite
ammonia
total inorganic
nutrient-N
sil icate
Elbe discharge
phytoplankton
diatoms
flagellates
1 ~ f <10
annual
frequency
f=1
10
~
2
25
8
20
16
35
95
21
52
41
36
4
2
34
26
28
41
37
1
18
14
11
7
24
22
13
36
11
35
35
23
21
16
13
14
5
31
37
23
2
31
39
36
39
36
66
9
9
f
Tab. 1: Portions of total variance in different frequency bands
7
:The Helgoland Reede time series exhibit for most of the parameters a decay in the short period part of the spectrum resembling that of temperature (Tab.2). It is only Elbe river discharge, silicate and nitrite which show a much stronger decay in
that part of the spectrum (the rates are -3.43, -2.13, and -2.11,
resp.). For Elbe discharge this means a strongly decreasing
,importance of short term events, for scales less than a month.
:For the other two parameters the situation is not clear.
0
In the frequency band from 1 to 10 cycles/year the decay rates
'are generally, except for nitrate and nitrate, smaller than -5/3.
They are relatively similar for sea surface temperature, and
,total nutrient-N. They are smallest for phytoplankton, especially
for diatoms (-0.5). In this range nearly all parameters'seem to
,be determined by processes which do not obey a -5/3 law.
;A more detailed discussion of interrelations of the parameters
'will follow, when the cross spectra and coherence spectra are
'available.
'parameter
,sea surface temperature
salinity
phosphate
nitrate
:nitrite
,alTlTlonia
:total inorganic nutrient N
,silicate
Elbe discharge
'phytoplankton C
,diatoms
flagellates
slopes in the frequency band
1<f<10
10~f
-1.4
-1.8
-1.7
-1.8
-1.8
-1.1
-1.0
-1.6
:"1.7
-1.1
-1.5
-1.3
-2.1
-1.9
-1.9
-2.1
-3.4
-1.5
-1.6
-1.7
-1.5
-0.9
-0.5
-1.3
Tab. 2: Slopes of variance spectra obtained by linear regression
analysis for different spectral bands
6. Acknowledgements
o
•
We are obliged to the technicians of the Biologische Anstalt
Helgoland for careful collection of the data, especially to E.-H.
Harms, P. Mangelsdorf, and K. Treutner. We like'to thank Prof.
Dr. M. Gillbricht (Biologische Anstalt Helgoland) and Dr. D.
Kohnke (Deutsches Ozeanographisches Datenzentrum) for making
:available the data used in this study. Many thanks are also due
,ta my colleague Dr. M. Bohle-Carbonell for his valuable comments
'during the editorial phase and to my student A. Moll for his
technical assistance.
8
•
7. References
•
•
BECKER, ,G., 1981: Beiträge zur Hydrographie und Wärmebilanz der
Nordsee.- DHZ 34: 167-262.
BECKER, G., & D. KOHNKE, 1978: Long-term variations of temperat ure and salinity in the inner German Bight.- Rapp. P.- v.
Reun. Cons. int. Explor. Mer, 172: 335 - 344.
BERG, J. & G. RADACH, 1985: Trends in nutrient and phytoplankton
concentrations at Helgoland Reede (German Bight) since 1962.ICES C.M. 1985/L:2, Copenhagen.
BIOLOGISCHE ANSTALT HELGOLAND, 1962 -1984: Jahresberichte. Hamburg.
GILLBRICHT, M., 1983: Eine "red tide~ in der sUdlichen Nordsee
und ihre Beziehungen zur Umwelt.- Helgoländer Meeresunters.
36: 393 - 426.
.
.
GILLBRICHT, M., 1986: Phytoplankton and nutrients near Helgoland.~ ICES C.M. 1986/L:20.
JENKINS, G.M., & D.G. WATTS, 1968: Spectral analysis and its
applications.- Holden-Day, San Francisco.
LUCHT, F., & M. GILLBRICHT, 1978: Long-term observations on
nutrient contents near Helgoland in relation to nutrient input
of the Elbe river.- Rapp. P.-v. Cons. int. Explor. Mer, 172:
358 - 360.
OKUBO, A., 1980: Diffusion and ecological problems: mathematical
models.- Spring:r-Verlag, Berlin Heidelberg New York, 254 pp.
PLATT, T., 1972: Lo:al p~ytoplankton abunjance and turbulence.Deep-Sea Res. 19: 183 - 187.
PLATT, T., &K.L. DENMAN, 1975: Spectral analysis in e:ology.Ann. Rev. Ecol. Syst. 6: 189 -210.
RADACH, G, & J. BERG, 1985: Trends in den Ko~zentrationen der
Nährstoffe und des Phytoplanktons in der Helgoländer Bucht
(Helgoland Reede Daten).- Berichte der Biologischen Anstalt
Helg~land, Nr. 2 (in p~ess).·
.
STRATHMA~N,
R.R. 1967; Estimating the organic carbon content of
phytoplankton from cell v~lume o~ plasma volume.- Limnol.
Oceanogr. 12, 411-418.
TO~T,
S., & T. PLATT, 1978: Fluctuations in the abundance of
phytoplankton o~ the California coast.- in: E. NAYLOR & G.
HARTNDLL, 1978: Cyclic p~enomena in marine plants and animals.
Pergamon Press, Oxford •
UTERMOHL, H. 1958; Zur Vervollkommnung der quantitativen Phytoplankton-MethJdik. Mitt. int. Ver. Limnol. 9, 1-33.
WEIGEL, H.-P. 1978; Temperature and salinity observations from
Helgoland Reede in 1976.- Annls. biol. Cons. int. Explor. Mer
33: 35.
9
CENTJCAROf
CENTJCAROE·
20
20
10
O-h!~""TFP1~Ill'll'Ir--''!l'IlT~:1!'r--r::rn:-"""'l'"Tln--""T!l7"r.-~'--''I!l'I''Ir-T:l1I''il'--'l'!'r'r--'
1~1I2
SURFRCE TEHPEARTUAE
HERN SERSONRL SIGNAL
CREWS OF M.B. 'ELLENBOGEN' RND 'RADE' I BAH
Fig. 1: Surface temperature at Helgoland Reede~ 23"years of data projected into one year:
a) all measurements b) mean annual cycle and standard deviations on the basis of the measurements of each day
0/00
35
a)
0/00
35
30
b)
30
......
,
'
:.,
...."
,
.
25 -tll
J stllj-,,",W-'"Imrr--n!mr"--rMllV-T'lI'I1C---nrn-"""'T!!1?"-IU"Ir-"m!'''--r.r1!'r-'''lJ''!''''--'
SALINITY
PROJECTED INTO 1 Y
B.HETSCHER. K.TREUTNER
I
'11'
SALINITY
HEAN SEASONAL SIGNRL
B,METSCHER. K.TAEUTNEA I SAH
SAH
Fig. 2: Salinity at Helgoland Reede, 23 years of data projected into one year:
a) all measurements b) mean annual cycle and standard deviations on the basjs of the measurements of each day
•
e
•
" . .3/~I!C
3000
",
,~)
""3/~EC
"
3000
e
b)
1500
o J,M,
o
ELBE CHARGE RT NEU DARCHAU
PAOJECTEO INro 1 Y
DTSCH, GEWAESSERKUNOL. JAHRS.
J N
IM'
ELSE CHARGE RT NEU DARCHAU
HEAN SEASONAL SIGNRL
orSCH. GEWAESSERKUNOL. JAHRS,
Fig. 3: Elbe d;scharge at Neu Oarchau, 23 years of data projected into one year:
a) all measurements b) mean annual cycle and standard deviations on the basis of the measurements of each day
HY G-AT I L
MY G-AT I L
2.50
2.50
a)
b)
1.25
IM'
PHOSPHATE - P
PAOJECTED IHTO l Y
E.H,HAAHS. P.HANGELSOCRF
I
SAH
PHOSPHATE - P
HEAN SEASCNAL SIGNAL
E.H.HARHS. P.HANGELSOORF I SAH
Fig. 4: Phosphate at Helgoland Reede, 23 years of data projected into one year:
a) all measurements b) mean annual cycle and standard deviations on the basis of the measurements of each day
MT G-RT 1 L
MT G-RT 1 L
60
60
a)
..
,
b)
30
30
,
.... ----
,
, , -,-, .
,"
, '
o-+,J=Rt-j,.,--..,........--.....".......-"""..--r."""'.--....,..,o=--~~- ....."..::...=.;:mr=--=">'T'"-.,.;,~-:;,"""'..--,
o
IOn
1112
NITRRTE - N
NITRATE - N
PRDJEC1ED IN10 1 Y
E.H.HRAMS. P.MANGElSOCRF I SAH
Fig.
5:
HEAN SEASONAl SIGNAL
E.H.HARHS. P.MANGElSOORF I BAH
Nitrate at He1go1and Reede, 23 years of data projected into one year:
b) mean annua1 cyc1e and standard deviations on the basis of the measurements of each day
a) all measurements
"T G-Ar I' L;
~
14
"T G-Ar I L
,
"
11
a)
b)
:" "
.
,',
2
2
\
\
,,
,
•,,
,,
,.
,
..... - ....... -,.,... ,
,
\
\
', ....... , ...
o
...,
......... ,
'....
NITRlTE - N
PAOJECTED INfO 1 Y
E.H.HAAHS. P.MANGElSOORF
HE AN SEASONAL SlGNAL
E.H.HAAMS. P.MANGELSOORF I SAH
SAH
6: Nitrite at He1g01and Reede, 23 years of data projected into one year:
b) mean annua1 cyc1e and standard deviations on the basis of the measurements of each day
a) all measurements
•
I
."
-,'--
, ",
",-- .. ,'''-
......."'u"'--'?P1"--""""'-""'T'[rnv-""T1Inr--..,
NITRITE - N
1
,,
---------------.--_.,-----
o -+-J=t-j-.............-""'"..---,"""..---r.H:nr...-......
J'r.U"'N.---r.J'r.Ul""L,..,
J
Fig.
-- ..... __ ."
" .... _,.-._ ... -- .... -' -".-
"
,,
•
,
,,
,
,
•
KT G-AT I L
30
a)
..
....
KT G-AT I L
30
e
b)
"
,
15 ." . .
•• 0°:.
'.
IS
, ,,' "
..
............. _-_ .... ' , ..... -...... " .. -_ ..
--- ... '
---.--- ... ........ -.......
RHHONIA
N
PACJECTED INTO I Y
E. H.HARHS. P.HANGELSOORF
o -h;;'M3r.N;-~nr--r,4JllI'-'11lI!rw---r,ü17-T'1i";;r-~;;;r-"T/llTI!""--rU"ll.-"'T1Ilrr---rtri'fii.-"'Tll1!"l""'--,
I
AHHONIR - N
HE AN SEASONAL SIGNAL
E.H.HAAH5. P.MANGEL500RF / SRH
SAH
Fig. 7: Ammonia at Helgoland Reede, 23 years of data projected into one year:
a) all measurements b) mean annual cycle and standard deviations on the basis of the measurements of each day
HT G-AT I L
HT G-AT I l
60
80
a)
•
b)
I
TOTAL INORGRNIC NUTRIENT
PROJECTED INTO.l Y
N03-N + N02-N + NH~-N
N
TOTAL INORGANIC NUTRIENT - N
HE AN SEASONRL SIGNAL
N03-N + N02-N + NH~-N
Fig. B: Total inorganic nutrient-N at Helgoland Reede, 23 years of data projected into one year:
a} all measurements b) mean annual cycle and standard deviations on the basis of the measurements of each day
tlT G-RT I L
tlT G-RT I L
110
110
a)
b)
'.
. . . , ..
'
.
. 20
20
,"._----, ..... ~'
,"
... _ _ .... , . . .
....... '
,
... tI'
o
SILICATE - SI
PROJECTED INTO I Y
E.H.HRRHS. P.MANGELSOORF I SAH
"
.-----_/
-.-
SILICATE - SI
HEAN SEASONAL SIGNAL
E.H.HARMS. P.MANGELSOORF I SAH
Fig.
9: Silicate at Helgoland Reede, 19 years of data projected into one year:
a) all measurements b) mean annual cycle and standard deviations on the basis of the measurements of each day
"f G I L
Hf eiL
10·
10'
,~ :"";4a):":iüi~~ti~~j~~~~~~~ii:::~:;;,.,,,;.
_c~~~"\·~1,"r·4'i1~~./;:,"'."':':f!:':~." ;..,:.:. =-:
...... ::.~ .....:.. )~"'f"(.I.~··.
b)
10'
':,{C;';:
·:.:;'"·:,:':~·.~':"')'t;,~;",,~'rJ~~.~'~·~.e
:: ~W~}~{t~(~~~~;'~;
'Xi/\iV/" 'T\' "''''~:'':'~~f;~~~{W~!~0~!~
.. . ..
. ......
...':' .
. ..
'
..
'
.'
•••••
...... ------_ ... '
"
"
" , ...... -----
10'
,
'
..... - ...... - .... '
-...... --
.. _---- .... --.
.. _---- .... --,
,-' "
0"
",
10·'
...,
10" +J"..N:r--..!"PIr--.""....- ............-"""'...--..."""::--...".".--.."""'-...........-~,....-"='."..-."..'T"---,
PHYTOPLANKTON - C
PACJECTED INHl I Y
H.GllLBRICHT. E.HAGMEIEA. K.TAEUTNEA
I
BAH
PHYTOPLANKTON - C
"EAN SEASONAL SIGNAL
M~GILLSA[CHT.
E.HAGMEIEA. K.TAEUTNER
I
SRH
Fig. 10: Phytoplankton at Helgoland Reede, 23 years of data projected into one year:
a) all measurements b) mean annual cycle and standard deviations on the basis of the measurements of each day
•
e
•
"' li I L
10'
b)
10'
,,
,,
,•
10'
,
,
,,
,,---.... ... .",,'-- ....... .,- .. ... ' ........
,,
"
10'
,,
-- ..... ,,
-_.--.-.-.".""--
10-\
OIATOHS - C
PROJECTEO INTO I Y
H.GILLBAICHT. E.HAGHEIER. K.TAEUTNER
I
OlRT0l15
C
I1EAN SEASONAL SIGNAL
I1.GILLSRICHT. E.HAGMEIER. K.TREUTNER
SAH
I
SAH
Fig. 11: Diatoms at Helgoland Reede, 23 years of data projected into one year:
a) all measurements b) mean annual cycle and standard deviations on the basis of the measurements of each day
"' li I L
'. .
10'
"T eIL
10'
".
::';:~'i/:~~0.iii~li~~f.~~i;~iit;~:;:.:,;:. .,; .,. .,: ·
b)
JO'
;;.-",> "
10'
loe
. .~;~~\·t·~~:·~.,;~~~t~·~?·~.',: 'i ~:::;..;;;:,::~ '.; ....~::.~~~~h~~t{.~:.:..-~~;·?\··"::;\·~·:~.C~~~~),:~:~i:~~· :"~~~~.;C":t.~"~'
;r0:~~~\~!~~~~~;~~'{~\Y~7~;:?~';>~).:!~;f:.~~r~~r~~[1~~.~
','
10-'
:"
.......
:. "
.... _--_ .......
10'
10'
,"'
'.
10" +JilWN-"TPrr-1iiI!_--I'IlII"....-rIür.r--'T"Tl'Iö:r--rrrn--""Tll;rnr-""T'l!rr-~"T""-TWr.;--IliF.,....-,
,.2
FLRGELLRTES - C
PROJECTED INTO 1 Y
H.GILLSRICHT. E.HAGHEIER. K.TREUTNER / SAH
FLRGELLATES - C
HE RN SEASONRL SIGNAL
H.GILLBRJCHT. E.HAGMEJER. K.TREUTNER
I
SAH
Fig. 12: Flagellates at Helgoland Reede, 23 years of data projected into one year:
a) all measurements b) mean annual cycle and standard deviations on the basis of the measurements of each day
VARIANCE
I'"
10-1
-.
I~
..
'0-'
10"
....
.... :.~:
.-.":.' :.....:.::.
..-.,....
. .' ~ .~..:: ;.. ~:~:;~.',(.:::.~ ...., ...
.~~~
,.~ .:..-:~~~~':~~
'.
• I
'~+----r--_--...---r
~
........-ro.........,...---_-_--.-,..-,~-ro~----'---'-W
~
SURFACE TEMPERATURE PATCHED
. :.:;;' ":.
__~..............,r---"-T"----r-_~-.--r-..........,
~
W
CYClES/Y
5-F. FG-10. P-.05
LG lTt -A'8-LG lXI
A- -1.1'15801
8- -0.611315
1I·-0.8:!3 P-0.050 "-'I
IIAIIOIl" 11 AT P.II -0.950
LG In -A'8-LG lXI
A- -1.663139
8- -1.'I13:!50
11--0. BI1 P·0.050 11-'11
IIAIIOIl" 11 AT P.II -0.301
Fig.
13:
LG In .A·hLG lXI
A- -1.010319
8. -1.190B6
11·-0.921 P.0.050 11-193
"AIIOO" " "T P.II -0.010
Variance spectrum of sea surface temperature
VARIANCE
The confidence intervall for each speclral value is illdlcated ill
the lower left; lhe regress ion 1ines for the 3 frequency bands
f<l. l<f 10. f<10 cycles/year are given togelher wHh the
number of values N and lhe significallce threshold of lhe
correlatioll coefficlent R.
1.1
I~
.. :
I'"
I~
.......,r----.---.--_...--........-.-~---...--.....---.---'r-.--.-...,...,..,.----_-_-.---.--.-.....-........,
I~-I-----.---.--r-........-r-.......
~
w
~
SAllNITY PATCHED
LG ITI-A'B_LG lXI
A- -1.8BB:!91
B- -0.961\31
11--0.9'16 P-0.050 11-'1
"AIIOOII" AT
-0.950
p."
S-f. fG-10. P-.05
LG lTl-A'B-lG lXI
A- -1.65'13'19
8- -I. 1\ 5B1'I
"--0.110 P'0.050 11-'11
"AIIOO" " AT P.II -0.301
Fig.
14:
Lli lTI -A'Bolli lXI
A- -0.981321
B- -1.1281'18
"--0.925 P-0.050 ..·193
"AHOO" " AI P.II -0.010
Variance spectrum of salinity
~
w
CYCLES/Y
VARIANCE
I"
I"
....
----..-_---:
.....
....
....
.....
.....
1....
+------.,...---..-.......-.,.-.,.................,..---....--.......-...--....-~ .................,---""'T""---.--.;.:....:41~...__.-.-r_---...-__.- ......._._...............'"'T""110' CYCLES/Y
1 , - 1 . . .
ELSE CHARGE AT NEU DARCHAU
'x.
lG !TI -A-8oLG
A- -2.2121D6
8- -0.80I7Q8
11--0.938 '-0.050 M-'
AANOO" R AT P.N -0.950
5-F, FG-10, P-.05
lG ITI -A-8oLG 'XI
A- -1.9909
8- -'.'768'9
11--0.852 '-0.050
AAMOO" R AT
-0.308
'.H
Fig.
15:
lG m-A-8oLG 'X'
A- 0.055806
11- -3.'29901
11--0.911 P-0.050 M-188
IIANDO" R AT P.N -0.010
N-.,
Variance spectrum of Elbe discharge at Neu Oarchau
VAR IANCE
11'
The confldellce inlervall fo,' each <,pectral valllc i5 indicated in
the 10wer len; lhe regress i Oll li nes for lhe 3 frcqllellcy hands
f<l, l<f 10. f<1O cyclt>5!yearare givcnlogelher wilh lhe
n",,,ber of villucs N alld lhe silJniricilnce threshold of lhe
correlatlon coefficient R.
.0'
Ie-'
I'"
I'"
'.
I....
.... ......
...
...:...... ~
10"
.
..::.~.;.~.:~:
,
".- ••
.'., .
-01'; ." .~ . . .
.•..
.0"
I"
101
PHOSPHATE - P PATCHED
lG!T, -A'8oLG .XI
A- -2. 99929Q
s- -0.082232
11--0.213 '-0.050 M-'
RANOO" A AT P.M -0.950
5-F, FG-10. P-.05
lG!T' -A'8oLG .XI
A- -Z.96830S
8- -1.039637
11--0.618 '-0.050 M-"
IIANOO" 11 AT '.H -0.308
Fig.
16:
LG lYt -A'8olG 'X'
A- -Z.OSQI9Z
8- -1.189383
11-·0.921 '-0.050 H-19Z
IIANOO" 11 AT '.H -0.010
Variance spectrum of phosphate
".; .. ' ...'
... .I.:.....,:.. ::-::.~.~~~.~!
. ..._.......;:..., : ..~._ ;, ß·...
'I~ '. ;~.l. .....
'i·f
-l-----...--,..---.---..--..--.-....-....----.----..-....---.---.--.--.-r---....---.-_~..._
I_ _
~--.--,..--.--..-...."r"I,, CYCLESIY
10'
VARIANCE
..I
. --
I"
....
....
•r'
I'"
....
....-1f - - - -.....10-
.......--.--.-...........,....,.-r---...---.-----..-............-..................---_._-_-....-....-''T_........~r_-- .........-__..-"T__.__.._.~ CYCLES/Y
I"
lG (TI.A-8.lG lXI
A- -D.05555Z
8- -0.6533611
R-·0.926 1'-0.050 N-"
RAHDDR A AT ".N -0.950
.01
.01
HITRATE - N PATCHEO
.0"
S-F, FG-IO. p•• OS
lG nl -A-8.lG lXI
A- 0.Z00106
8- -1.5688611
R--0.859 1'-0.050 H-III
RAHDD" R AT P.N -0.308
Fig.
17:
lG!TI -A'8olG lXI
R. 0.6511Z95
8· -1.8021116
R·-0.912 1'-0.050 H.19Z
RANDO" A AT P.N '0.010
".
Variance spectrum of nitrate
VARIANCE
The confidence intervall for each specLral value is indicaled in
the lower lefl; Lhe regress ion 1ines for Lhe 3 frequency hands
f < 1, 1 < f 10, f< lU eye les/year are 9 iven togeLher wi Lh Lhe
number of va lues N and lhe si gn i f icance lIll'esho 1d of lhe
eorrelalion coefficient R.
, ..I
10'
I'"
....
10"
I'"
I'"
....-t----.......- ......- r - " T - - -........-.-r--:---.--__--r-..-.-.--.........,
..-I
NITRITE - N PATCHED
lG nl ·A·BolG lXI
A- -Z.0915111
8- 0.308315
H·0.6n 1'-0.050 N.II
HRHDD" ART ".N -0.950
I"
S-F. FG.IO, P•• OS
lG !T1-A-8.lG IX'
A- -1.9Z5515
8- -1.1196511
R-·0.893 1"0.050 H.III
HANDO" H AT P.N -0.308
Fig.
--...._--._......--.---.-
. .I
18:
e
lG ITI -A-8olG IX'
R· -1.35'166'1
8· -2.131'159
H··O. 9~ I 1"0.050 N.19Z
RRNOD" R RT P.N '0.010
Varianee spectrum of nitrite
:-.--_-....-....-"T_............' ,I CYCLES/Y
"I
..
VARIANCE
.1-
...
....
....
....
.'
•1"
....
....+---...:......,...-----.--.........--.-............---...--...--..-...-.,......,--.-....----.----.--...--.-.....-.,..............,,....----.---...--.--.--.-..............., CYCLES/Y
~.
~
~
AHHOHIA - N PATCHED
LG lTl -A·8.lG lXI
A- -0.819029
I- -1.111362
R--0.751 P-0.050 11-'11
RAIIOOll A AT P.ll -0.301
Fig.
19:
LG lYt -A'I.LG lXI
A- O. 116936
8- -1.8'11262
1I-·0.9n P·0.050 11-192
RAllOo" fI AT P.ll -0.010
Varianee speetrum of ammonia
The eOllfidenee inlervall for eaeh speelral vaille is indiealed in
the lower lert; lhe regr'cssiOll lilles for '-he 3 frC'l/lIcncy halids
f<l, l<f<10, f<1O cyclps/ycar aroe yivcn loyclhcr wilh lhe
number of vallIes N alld the sigllifieanee lhreshold of lhe
eorrelation eoefficient R•
VARIANCE
...
~
5-F, FG-10. P-.05
LG 1TI -A'8.lG lXI
A- -1.0538q7
I- - I. OQ'l023
R--0.988 P-0.050 11-"
RAllOOR R AT P.ll -0.950
.1-
~
.-
.1"-
....
....
....
. . . .: -
•
• e •• '.
o.
t_
..
.: ....., ....."". 0. ~ r:~ ~~
•
0.:.. -:_
e•
;. ..;:':~~~..
..
" : 1 . .,...... : ••
•1"
....+----...--...---.--.........--.-............---...--...--..-...-.--.--.-....----.---.--...-...--.-..-.-.-r------..--..-....--.--.--.-.-.-, CYCLESIY
.1"'.
IgII
10'
TOTAL JNORGANIC NUTRJENT - N PATCHED
LG lTl -A'8.lG IXI
A- -0.007198
B- -0.7301'1'1
11--0.931 P-0.050 11_'1
RAllOOll R AT P.ll -0.950
5-F, FG-IO. P-.05
LG lYt -A·8.LG lXI
A- 0.28Q'lQ9
I- -1.Q65816
11-·0.850 P-0.050 11-'11
IIAllOoll fI AT P.ll -0.308
Fig.
20:
LG lTJ -A'8.lG lXI
A- 0.896022
U- -I.U659Q]
A--0.922 P-0.05o 11-192
AAllOo" fI AT P.ll -0.010
Variance spectrum of total inorganic nutrient-N
10'
10'
VARIANCE
..
••1
...
-----------
.,..
....
. ".- :'.•
-.
•
.
: : : - .....
~.f'••••• • 01':... :
........-
__
.:•
....
....
....+-----.----.-...............
.0
-.-"?"'""O........ . - - - - - . - - - - . - - . . . _ _ . . . . . - . . . . . . . . ,........""T""T
ur'
.11'
SILICATE - SI PATCHED
.0'
.0.
5-F, FG-1D, P-.05
LG (Tl -A'hLG 'XI
A- -1.32118
8- -1.601559
11--0.996 1'-0.050 11-3
IIAND"" " AT ".11 -0.997
LG 1TI -A-S.LG 'X'
A- -0.238823
LG 1TI -A-8.lG 'XI
A- 0.816Z83
I- -Z.1099Q
11--0.936 1'-0.050 N-651
IIANo,," 11 AT "." -0.011
I- -1.ZSlq91
11--0.188 1'-0.050 N-n
IIANO"" 11 Al ".N -0.339
Fig.
21:
Variance spectrum of silicate
VARIANCE
The confirlence intervall for each spectral value is indicaLed in
the lower len; Lhe regt'ess ion I ines fur the 3 frequency hands
f<l, l<f 10, f<1O c,ycles/year are givcn togeLher wiLh Lhe
number of values N and lhe significance threshold of Lhe
correlalioll coefficienL R•
••1
."
....
....
....
....
....
---.-~......._ _...,..---...---...---~_
. .............., CYCLES/Y
1
..
..,
• •-:-."'?"_"""'---"...... •.'
."
...
I
....-1------.....-.
. . . . . . --.--.. . . -r-------.,.---~ . . . . . . ...._,.---__- ......-.....__._.. . . . . . .~r__--_.._.......-_._
.r
.0'
l
.01
...
PHYTGPlANKTGN - C
LG 'TI -A'hLG 'XI
A- -1.012003
I- -0.SQ6861
A--0.858 1'-0.050 "-,
IlANO"" " AT ... " -0.950
5-F, FG-10, "-.05
LG lTI -A'8.lG 'X,
A- -0.10888
I- -0.889133
11--0.655 1'-0.050 "_Ql
IIA"OO" 11 AT P.N -0.301
Fig.
22:
LG ,TI -A-8.lG 'X,
A- -0.03QQIQ
I- -1.516189
1I--0.88Z 1'-0.050 N-792
IIANoO" 11 AT P.N -0.070
Variance spectrum of phytoplankton
.................. CYCLES/Y
.0.
....
...
VARIANCE
'
.
...
....
..
L...
.
tu
• -.
·c.-. -. -. .
~
.r-
.... +-----..--~--. .......~....,....,~---..---.----.-..-- ......~...-r----.--_._-T___._...__""T'""r_--__._-__.-_.__._""T'""
~
~
~
OIAl«!"S - C
lG '" -A'8-lG ,X,
A- -0.176Q32
11- -0.219351
ft--0.35'1 P-0.050 N-.
AANlION ft AT P.N -0.950
~
................., CYCLES/Y
~
5-F. FG-IO. P-.OS
lG IYI-A'8_lG 'X'
A- -0.278205
11- -0.q95766
ft--0.Q66 P-0.050 N-~'
ftANOON ft Ar P.N -0.3011
Fig.
23:
lG IYI ·A'8-lG 'X'
A- 0.810196
11- -1.58179~
ft--0.887 P-0.050 N.792
ftANOON ft AT P.N -0.070
Varianee speetrum of diatoms
The eonfidence intervall fur each speelral value is inclieated in
the luwer lett; the regress iOll 1ilies for I.he 3 fre'luency hands
f< 1, 1 < f to, f (10 cye lec;/year are gi vell logelher wi lh lhe
I1lIßlber of values N alld lhe signifieallce lhreshold of lhe
eorrelation coefficient R•
VARIANCE
'.'
...
....
....
....
....
....
•r-+------..--~--........-....,....,~---..---.---.-..--..-._.____r---""T'""-~-....___._..._
~
~
w
FLAGELLAlES - C
lG ,Tl -A'8-lG 'X,
A- -0.550952
0- -0.192559
ft·-0.812 P.0.050 N."
ftANOON ft AT P.N -0.950
S-F. FG-I0. P-.OS
lG IYI .A'O-lG 'X,
A- -0.079211
0- -1.310211
ft--O.OIQ P-0.050 N-Ql
ftANOON ft AT P.N -0.300
Fig.
24:
lG ITl .A·O_lG IX'
A- 0.529212
87113
A·-0.90Q P.0.050 N.787
AANOON ft AT P.N '0.010
.'.1\
Variance spectrum of flagellates
.............,r__--_._-.......-..._""T'""_.__........____, CYCLES/Y
~
~