Reconstructing Past Environments: Paleoecological Transfer Functions
Deborah Balch
University of Arizona
Humans have long recognized the relationship between fossil organisms and past environments. For
example, in Ancient Greece, Xenophanes and Herodotus found marine fossils far inland and deduced that
the area must have been an ocean in previous times (Imbrie and Newell, 1964). Paleoecologists use this
same concept as the basis for their scientific research. They use the fossil record to reconstruct past
environments and climates.
One way this is accomplished is by studying modern assemblages and their environmental preferences and
correlating this with their fossil assemblages. As an example, imagine taxa assemblage “X” is always
found in environmental conditions termed “Y”. If we find this same assemblage in the fossil record, we
can deduce that the environmental conditions at that time in the past were similar to “Y”.
This concept has been quantified in a method called paleoecological transfer functions. The first step to
building a transfer function is to develop a training set. Training sets are composed of two sets of data:
measurements of the environmental parameter (i.e. temperature, pH, salinity, etc.) and abundance of its
associated taxa assemblage. These data are then developed into a set of equations (called transfer
functions) that correlate the biological and environmental data. These equations often take the form:
Tm=XFm and Tp=XFp
T is the estimated environmental parameter (m=modern, p=paleo), F is a matrix of modern and fossil data
and X is a transfer coefficient or set of coefficients (Imbrie and Kipp, 1971; Hutson, 1977). Calibration is
accomplished by solving this equation for X with a set of biological data (F) and observed values of the
environmental parameter (T). Once calibrated, the transfer function is applied to the fossil assemblage and
the paleoenvironmental parameters can be estimated. There are several different computational techniques
available to reconstruct past environments through the use of transfer functions (refer to Sachs et.al, 1977
for a comprehensive list).
This summer, my research focused on collecting data for a training set which will be used to reconstruct the
past environments of Lake Malawi using modern ostracode assemblages. From July 8 to August 3rd 2001,
I collected data from various small lakes and ponds in areas around Kigoma and Sibwesa, Tanzania (Table
1). In the field, I measured water temperature, dissolved oxygen, pH, conductivity, turbidity and depth.
Water and surface sediment samples were taken back to the lab for further analysis. Water samples were
analyzed for total phosphorus, PO4-P, NH4, NO3-N, NO2, Alkalinity and SiO2. The surface sediments
were analyzed for % organic carbon and ostracode abundances. Please refer to Table 2 for all results
(except ostracode counts, which remain to be analyzed).
It is very important that a training set is entirely representative of the fossil assemblage and that no-analog
conditions are avoided (Huston, 1977). Therefore, these data are just the beginning component to a large
training set that will incorporate samples from many locations in Kenya, Tanzania, and Malawi. The
transfer function, once computed and calibrated, will be applied to fossil assemblages found in long cores
taken from Lake Malawi (drilling is projected for February 2003). After all of the analyses are complete, it
is our goal to obtain a profound understanding of the Quaternary environments of Lake Malawi and to use
this information to predict how the lake may be changing due to recent anthropogenic activities.
Table 1: Sites sampled in Summer 2001
Site
Site 1
Name
Ujiji Beach
Latitude
o
4 55.189s
o
Longitdue
Date
Time
Weather
o
8-Jul-01
4:30pm
clear sky, slight breeze
o
8-Jul-01
20-Jul01
20-Jul01
20-Jul01
20-Jul01
27-Jul01
27-Jul01
27-Jul01
27-Jul01
3-Aug01
3-Aug01
3-Aug01
3-Aug01
3-Aug01
4:55pm
clear sky, slight breeze
10:08am
hazy, slight breeze
10:29am
hazy, slight breeze
1:10pm
sunny, hot with breeze
1:52pm
sunny, hot with breeze
10:37am
cloudy, slight breeze
12:13pm
cloudy
4:05pm
partially cloudy
5:13pm
partially cloudy
10:08am
sunny, very windy
10:40am
sunny, wind was blocked from vegetation
12:00pm
partially cloudy, wind
12:41pm
partially cloudy, wind
3:10pm
sunny, slight wind
29 40.393e
Site 2
Ujiji Beach, 100m south of site 1
4 55.189s
29 40.420e
Site 3
Katobelo Lake, Sibwesa
6o29.251s
29o57.519e
Site 4
Katobelo Lake, 200m SW of site 3
6o29.307s
29o57.741e
Site 5
Kabogo Lake, Sibwesa
6o28.968s
29o58.830e
Site 6
Kabogo Lake,300m south of site 5
6o29.033s
29o59.005e
Site 7
Nyakubeleka Lake, near Burega
4o54.525s
29o38.938e
Site 8
Katosho Lake, near Butanga
4o50.930s
29o39.349e
Site 9
Site
10
Site
11
Site
12
Site
13
Site
14
Site
15
o
o
Kikamba Lake
4 54.473s
29 37.109e
small empheral pond east of airport
4o53.273s
29o41.879e
Nyakubeleka Lake, deeper sample
4o54.567s
29o38.971e
Nyakubeleka Lake, offshore sample
4o54.536s
29o38.934e
o
o
Katosho Lake, deeper sample
4 50.901s
29 39.357e
Katosho Lake, other side of lake
4o50.997s
29o39.526e
Kikamba Lake, deeper sample
N/A
N/A
References
Hutson, W.H., 1977. Transfer functions under no-analog conditions: experiments with Indian Ocean
planktonic foraminifera. Quaternary Research 8:355-367.
Imbrie, J. and N.G. Kipp. 1971. A new micropalaeontological method for quantitative Paleoclimatology:
application to late Pleistocene Carribean core V28-238. In:
The Late Cenozoic Glacial Ages (K.K. Turkian ed.) Yale University Press, New Haven:77-181.
Imbrie, J. and N. Newell. 1964. Approaches to Paleoecology. John Wiley and Sons Inc., New York.
432p.
Sachs, H.M., T. Webb III and D.R. Clark., 1977. Paleoecological transfer functions. Annual Review of
Earth and Planetary Sciences 5:159-178.