Supporting information
S1 – Chronology of the Lake Katinda record
The chronology of the uppermost sediments is based on 210Pb-dating of core 01-1P (Fig. S1-1
and Bessems, 2007), which we transferred to 07-1P using shared marker horizons of magnetic
susceptibility and bulk composition. Sediment ages at depth and accumulation rates were
calculated using the constant-rate-of-supply model (Binford, 1990).
2000
Median year of deposition
1980
1960
1940
1920
1900
1880
1860
1840
0
20
40
60
80
100
depth (cm)
Fig. S1-1 Age-depth relationship in the uppermost sediments of Lake Katinda, based on 210Pb
dating (2 SD error bars indicated).
The chronology of deeper sediments is based on
14
C-dating of core 02-1P (Bessems, 2007).
High-quality terrestrial macrofossils being scarce, the age model is built from
14
C dates on
bulk organic matter, corrected for an assumed constant old-carbon age offset. The offset
1
value used (589 years) is the mean value of four estimates, obtained by subtracting the 14C age
of three terrestrial macrofossils and one
210
Pb-dated interval from bulk-organic
14
C dates at
the same depth (Table S1-1). The corrected 14C ages were then converted to cal yr BP (Table
S1-2) following Reimer et al. (2009). Two dates (at 178 and 236 cm) appearing much too
young were excluded (Fig. S1-2).
Depth
(cm)
Lab code
30.5
30.5
pwradlab
Poz-9839
178
Raw 14C age
Age offset
- 210Pb dating
- bulk organic mud
150*
700
550
Poz-20229
- terrestrial plant
macrofossils
545
178
Poz-18579
- bulk organic mud
1025
236
Poz-19310
- terrestrial plant
macrofossils
745
450
236
Poz-18625
- bulk organic mud
1195
_
540
Poz-20286
- terrestrial plant
macrofossils
2370
875
540
Poz-18580
-bulk organic mud
3245
_
Material dated
480
Table S1-1 14C and 210Pb dates used to calculate the old-carbon age
offset. *Interpolated 210Pb date converted to raw 14C date.
Depth
Raw
Lab code Material dated14
(cm)
C age
SD
30.5*
119
178**
236**
400
540
602
780
30
30
30
30
35
35
30
40
Poz-9839
Poz-16502
Poz-18579
Poz-18625
Poz-16549
Poz-18580
Poz-18581
Poz-4599
bulk organic mud
bulk organic mud
bulk organic mud
bulk organic mud
bulk organic mud
bulk organic mud
bulk organic mud
bulk organic mud
700
1320
1025
1195
2690
3245
3410
4090
Corr. Cal yr
age BP
14C
111
731
436
606
2101
2656
2821
3501
114
677
502
603
2073
2778
2923
3773
Min age Max age
(2 sigma)
12
664
338
543
1989
2544
2847
3645
(2 sigma)
269
687
532
655
2291
2924
3019
3880
Table S1-2 Calibrated 14C ages used to calculate the age-depth relationship for Lake
Katinda sediments. *Replaced by 210Pb date. **Dates excluded from age
model.
2
depth (cm)
0
100
200
300
400
500
600
700
800
0
500
cal yrs BP
1000
1500
2000
2500
3000
3500
4000
Fig. S1-2 Age-depth relationship in the main sediment sequence of Lake Katinda,
based on 14C dating of bulk-organic matter corrected for a constant oldcarbon age offset, with error bars indicating 2-sigma error ranges. Crosses
indicate dates excluded from the age model; the open symbol is a date
replaced by the corresponding 210Pb date.
S2 – Age-depth modeling and correction for the compaction gradient in Lake Katinda
The used age model is based on the total of 13 210Pb-dated intervals (0-43 cm), five 14C dates
(43 cm to the base of 02-1P at 780 cm), and the surface tie-point of core 01-1P (January
2001).
Water-content variation (Bessems, 2007) reveals a compaction gradient in the
uppermost 50 cm (cf.
210
Pb dates and Fig. S1-1), and a second section of uncompacted
sediments around 260-280 cm (ca. 1500 cal yr BP, Fig S2-2). High-amplitude lake-level
fluctuations in climate-sensitive tropical lakes such as Katinda cause significant variation in
conditions of mid-lake sedimentation, which affects both dry-sediment composition and water
content (e.g. Verschuren, 2001), and thus also the relationship between charcoal abundance
3
and charcoal flux. To correct for such bias, we considered different age-depth models to
account for the probable variation in sediment accumulation suggested by sedimentological
changes through the sequence, using CLAM (Blaauw, 2010). In total, we considered 15
different age-depth models (Table S2-1), on either linear depth or accumulated dry mass
scales, and with a variety of smoothing parameters. Models or smoothing values producing
chronological inversions were excluded. In general, the greatest differences between the
different age models occur in the upper meter of the sequence, due to a slope change between
the 14C date at 119 cm and the 210Pb-dated section.
Type
Interpolated
Polynomial
Polynomial
Polynomial
Smooth spline
Smooth spline
Smooth spline
Smooth spline
Interpolated
Polynomial
Polynomial
Polynomial
Smooth spline
Smooth spline
Smooth spline
Y axis
Linear cm
Linear cm
Linear cm
Linear cm
Linear cm
Linear cm
Linear cm
Linear cm
g dry mass/cm2
g dry mass/cm2
g dry mass/cm2
g dry mass/cm2
g dry mass/cm2
g dry mass/cm2
g dry mass/cm2
Parameter
_
3
4
5
0.5
0.6
0.7
0.8
_
3
4
0.7
0.8
0.85
0.9
Tab S2-1
The resulting differences in CHAR estimation are reported in S3. The final age-depth model
(Fig S2-2) is a smoothed spline based on cumulative dry mass with smoothing parameter 0.8.
This model treats changes in sedimentation rates rather conservatively, and results in a good
temporal match between the local (Lake Katinda %CaCO3) and regional (Lake Edward %Mg)
evidence of climatic drought episodes (Fig. 2, main text).
4
Fig S2-2 The selected 0.8 smoothed-spline age model based on cumulative dry mass.
S3 – Estimation of confidence intervals for the Katinda charcoal influx
We tested the extent to which the 15 different age-depth models (S2) change the temporal
patterns in charcoal flux values, producing 95% confidence intervals (Fig S3-1). This
demonstrated the robustness of fire increases around 2170 cal yr BP and after 1750 AD, and
of the multi-century cycles between those two dates (Fig. 2, main text).
5
Fig S3-1: 95% C.I. on charcoal flux according to different age-depth models, versus linear
core depth.
S4 - Chronology of the Lake Naivasha record, and charcoal influx estimation
The chronology of the Lake Naivasha sequence is anchored at 18 depth intervals in addition
to the sediment-water interface (Table S4-1). This total includes eight
macrofossils from core 93-2L (Verschuren, 2001), and 10
210
14
C dates on plant
Pb-dated intervals in NC93-1S
(Verschuren, 1999), transferred to NC01-1P using eight tie points based on LOI variation and
three layers with Salvinia debris (Mergeay et al., 2004).
For the final age model, we linearly interpolated between the dated intervals as in
Verschuren et al. (2000), to account for substantial variation in sediment accumulation
through time.
Charcoal concentrations per volume (particles/cm3) were obtained by
converting sample wet weights to corresponding volumes, using the dry/wet ratio and a
regression of porosity vs water content based on core NC 91-S. Charcoal influx values
(particles/(cm2*yr) were then calculated by dividing volumetric concentrations by the
depositional time (yrs/cm) of the interval, as derived from the age-depth curve.
6
Lab code or depth
below lake surface
(cm)
Corrected depth
(cm, center)
Age (cal yr AD)
NC01-1S 0
NC01-1S 22
NC01-1S 30
NC01-1S 40
NC01-1S 54
NC01-1S 66
NC01-1S 80
NC01-1S 92
NC01-1S 102
NC01-1S 124
NC01-1S 144
NC93-2L 1831
NC93-2L 1855
NC93-2L 1889
NC93-2L 1965
NC93-2L 2009
NC93-2L 2033
NC93-2L 2066
NC93-2L 2188
-3
19
27
37
51
63
77
89
99
121
141
339
363
397
473
513
537
569
691
2001.4
1993.4
1988.4
1982.0
1967.8
1954.9
1938.4
1917.2
1890.5
1838.1
1818.7
1530.0
1436.0
1400.0
1278.0
1229.0
1011.0
891.0
600.0
Table S4-1
S5 - Multivariate and wavelet analyses
Underlying gradients in the pollen data set were extracted with indirect gradient analysis
(Birks & Gordon, 1985) using Canoco 4.5 (ter Braak & Smilauer, 2002). We used a total of
50 and 62 pollen samples for Lake Katinda and Lake Naivasha, respectively. The pollen sum
excluded pollen of aquatic plants, Cyperaceae (which are mostly derived from lakeshore
sedges) and spores of ferns and mosses. Preliminary Detrended Correspondence Analysis
(DCA) revealed that the pollen datasets from both lakes fit a linear rather than unimodal
model (1.8 SD for Lake Katinda; 1.4 SD for Lake Naivasha). Therefore, we preferred PCA to
DCA (Birks & Gordon, 1985), using untransformed pollen %, with species scores divided by
SD, focus scaling on inter-species correlations and centering by species. Samples and species
scores are reported in Fig. S5-1.
7
Fig S5-1 Principal Component Analysis (PCA) plot for Lake Katinda and Naivasha. Sample
symbols reflect the pollen zones (Ssemmanda et al., unpublished). For Lake
Katinda, pollen zone 1-2 corresponds to woodlands and forest with Celtis,
Acalypha and Urticaceae, pollen zone 3 to the shrublands/savanna transition and
pollen zones 4-5 to the expansion of savannah grasslands. Pollen zonation for Lake
Naivasha follows Lamb et al. (2003).
8
Finally we used wavelet analysis (Torrence & Compo, 1998) to assess changes in the
frequency of burning during the last 4000 years at Lake Katinda. Charcoal influx values (Fig
2c) were resampled at the mean sample resolution (5 yr) to gain an evenly spaced interval.
We used a Gaussian curve which best fitted the spiky nature of charcoal peaks, 8 parameters,
and a power-of-2 = 6 (Fig 2d, main text).
S6 Charcoal morphology analysis
To support our arguments on the provenance of recovered macro-charcoal we analyzed the
morphology of charcoal particles at the transition between forest and savanna (Fig S6-1 and
Fig. 2e, main text). Aspect ratio, thickness and presence of stomata (Umbanhowar &
McGrath, 1998; Wooller et al., 2000; Wooller, 2002; Jensen et al. 2007) of most fragments
(>80%) are indicative of savanna fire, with a minor contribution (10-20%) of woody
vegetation (Fig. S6-1 and 2, analyst: Giorgia Beffa).
Fig S6-1. Charcoal morphology at three levels in the Katinda sequence. (a) around 2700
cal yr BP; (b) the initial (aborted) expansion of grasslands around 2550 cal yr
BP; (c) final expansion of grasslands around 2150 cal yr BP.
9
% grass charcoal
100
75
50
25
0
2000
2500
3000
3500
4000
cal yr BP
Fig S6-1. % of grass charcoal between ca 3800 and 2000 cal yrs BP. The period around
2550 cal yrs BP has been analyzed every cm (total of 25 samples, see Fig
2C2, main text).
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