### 5.4.5 Zone 3: 700 – 129 cal yr BP

*Alchornea* and *Elaeis* dominated this zone though following an opposite trend. *Elaeis* reached its highest value (12%) while *Alchornea* decreased steadily (minimum at 4.5%). *Syzygium* remained well represented (2%). Among read swamp populations, *Typha* increased remarkably, up to 35% and Cyperaceae decreased (7%). NPPs were dominated by *Tetraedron* (up to 90%) and *Botryococcus* (up to 60%).

### 5.4.6 Zone 4A: 129 – 14 cal yr BP

This zone is characterized by the massive increase in Poaceae (90%) and the correlative decrease in *Typha* (17%). The percentages of *Elaeis* remained at the level reached in the previous area (7%). *Botryococcus* almost exclusively dominated the algae assemblage. This zone is also characterized by the noticeable presence of fungi.

### 5.4.7 Zone 4B: 14 cal yr BP – Modern

This zone differs from the previous one by the appearance of *Casuarina equisetifolia*, which reaches up to 16%. Poaceae decreased to 55%, in contrast to *Typha*, which increased to values above 30%. *Botryococcus* totally dominated the assemblages of algae.

## 5.5 ENVIRONMENTAL RECONSTRUCTION AND DISCUSSION

### 5.5.1 The decline in tropical humid plant taxa

Figure 3 is the graphical representation of a correspondence analysis using the microfossil assemblages for the environmental evolution of the Mboro-Baobab area. Three groups of taxa emerge from this analysis. The first is dominated by tropical humid (Guinean) tree taxa (e.g. *Dictyandra*, *Macaranga*, *Mallotus*, *Syzygium*, *Uapaca*), the second group is a mixture of taxa from trees and herbs of drier, Sudanian, phytogeographical affinity or having a wide spatial distribution (e.g. *Alchornea*, *Asteraceae*, *Celtis*, *Mitracarpus*). The third group is dominated by herbs found today in dry places in the Sahara and Sahel (e.g. *Aerva lanata*, *Tribulus*, *Amaranthaceae*). Only few trees are found in this group (e.g. *Acacia*, *Adansonia digitata*).

The most striking result of the analysis of these groups is the major environmental change revealed at 3200 cal yr BP (Figure 4A). The most humid tree taxa (group 1) which dominated earlier in the record, and particularly around 3875 cal yr BP (Figure 4B), dramatically declined in favor of drier plant taxa (group 2). This decline continued into the late Holocene in two main stages respectively around 2500 and 1300 cal yr BP. Contrasting with this step-like evolution of forest diversity, the regional, dry elements (group 3) exhibit a slow increasing trend starting from 3700 cal yr BP and peaking around 1600-1300 cal yr BP.

### 5.5.2 Changes in the hydrological regime

The 3200 cal yr BP event closely matches a major change in the hydrological regime (Figure 4C): changes in the algal community show that the lowering of the water level was initiated as soon as 3750 cal yr BP (cf. expansion of *Tetraedron*, Figure 2). At 3200 cal yr BP, the development of the oligotrophic algae *Botryococcus* (Figure 2 and 4C) mark the reduction in nutrient supply due to increasingly dry conditions, which culminated during the last millennium. The strong decline in the freshwater algae *Pediastrum* and *Coelastrum*, followed by the development of *Typha* populations, confirms this major change in the hydrological regime and the lowering of the lake level.
<figure><img src="image_25.png" /><figcaption>**Figure 3.** Correspondence analyses on the Mboro-Baobab pollen counts allowing distinction of tree main groups of taxa according to a decreasing humidity gradient. These groups define three periods (in bold).</figcaption></figure>

### 5.5.3 Timing of the end of the AHP in the Sahel

Earlier work by Lézine (1988, 1989) in the Niayes suggested the sudden disappearance of the gallery forests around 2500 cal yr BP as illustrated at Diogo, only a few kilometers north of Mboro (Figure 1A). Diogo illustrates the magnitude of this environmental crisis by showing the drop in the water level allowing for the development of a Cyperaceae swamp contemporaneous with the collapse of most of the trees, which established during the AHP (Figure 5). Only swamp forest (*Syzygium*) and pioneer (*Alchornea*) trees were able to persist in a context of increased dry conditions (Braconnot *et al.* 2019).

Our Mboro-Baobab record does not show such an abrupt shift from a humid to a dry environment. The tree cover (AP%, cf. Lézine *et al.*, this issue) was never highly developed, probably due to the distal position of the site with respect to the core of the Niaye groundwater system (Diogo) (Putallaz 1962) and seems to have only slightly varied over the last 4300 years (Figure 2). Forest composition however strongly changed. Guinean taxa underwent a clear phase of expansion centered at 3875 cal yr BP. A similar phase of development of tropical trees is seen at Jikariya (Waller *et al.* 2007) in the Manga grasslands of northern Nigeria between 3800 and 3500 cal yr BP that points to the regional character of this short phase of forest recovery. At Mboro-Baobab, this forest phase ended rapidly with steppic conditions increasing as soon as 3750 cal yr BP. Interestingly, this increase in aridity did not have an immediate effect on the composition of the forest gallery but probably only on its density. It is only at 3200 cal yr BP that the replacement of the wettest forest elements by forest taxa more adapted to drier climatic
<figure><img src="image_26.png" /><figcaption>**Figure 4.** Summary of the evolution of the environment at Mboro-Baobab over the last 4300 years. (A) Percentages of the three groups of pollen taxa revealed by the CA statistical analysis; (B) influx values of these groups; (C) influx values of the algae *Pediatrum*, *Coelastrum* and *Botryococcus*. The gray bars (from dark to light) show the progressive decline of the most humid elements. The dotted line shows the onset of dryness in a still humid context. Note that curves are superimposed and not cumulative.</figcaption></figure>

<figure><img src="image_27.png" /><figcaption>**Figure 5.** Percentage pollen diagram of main taxa from Diogo in the Niaye area of Senegal (Lézine 1988).</figcaption></figure>
conditions occurred. This replacement was not as abrupt as at Diogo but its amplitude was not negligible as shown by the decrease in percentages of group 1 by about 10% (Figure 4A). Taking into account the chronological uncertainties between sites, our Mboro-Baobab record closely fits with that of Jikaryia, which dates the decline of tropical humid trees at 3150 cal yr BP.

## 5.6 CONCLUSION

As already noted by Waller *et al.* (2007), significant differences in the timing and amplitude of similar events may occur in pollen records from the same region. The size of the sites and their location with respect to groundwater availability are among the parameters that can influence the local response of plants to climate change in terms of amplitude and timing. Compared to the other Niaye sites (Lézine 1988) Mboro-Baobab contains the most complete and detailed record of the end of the AHP. Despite its location on the edge of the wettest zone of the Niayes region, where the forest gallery was only poorly developed, it has undergone profound environmental changes allowing distinction of the successive phases in the establishment of the modern landscape. The drying of the Mboro-Baobab landscape was gradual, starting from 3750 cal yr BP then culminating at 1300 cal yr BP. In contrast, a major shift in the lake system and the forest diversity occurred at 3200 cal yr BP, marked by the lowering of the water level and the sharp decline of the tropical humid forest elements. The species turnover initiated at that time continued up to 2500 cal yr BP. Our results are consistent with those obtained in the central Sahel, which place the end of AHP between 3300 and 3150 cal yr BP depending on the site (Salzmann and Waller 1998; Waller *et al.* 2007). According to our study, the end of AHP (i.e. the retreat of the most humid elements from the gallery forests of the Niayes region) lasted about 700 years between 3200 and 2500 cal yr BP. The duration of this transition period was likely favored by the presence of a water table close to the surface, which was able to maintain humid conditions for several centuries after the major event of 3200 cal yr BP.

## ACKNOWLEDGEMENTS

This work is an “ACCEDE” Belmont Forum contribution (18 BELM 0001 05). Thanks are due to the Institut de Recherche pour le Développement (IRD) and the UCAD Geological Department (Dakar, Senegal) for logistic support in the field and authorizations and to the ECLAIRS International Laboratory (Dakar) and the LOCEAN Laboratory (Paris) for funding. KL and AML are funded by CNRS, France.

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CHAPTER 6

# Changes in the West African landscape at the end of the African Humid Period

Anne-Marie Lézine & Kévin Lemonnier

*Laboratoire d'Océanographie et du Climat, Expérimentation et Approche numérique/IPSL, Sorbonne Université, CNRS-IRD-MNHN, Paris, France*

Martyn P. Waller

*Department of Geography and Geology, Kingston University London, Kingston upon Thames, Surrey, United Kingdom*

Ilham Bouimetarhan<fnref n="1" /> & Lydie Dupont

*Center for Marine Environmental Sciences, MARUM, University of Bremen, Bremen, Germany*

African Pollen Database contributors<fnref n="2" />

**ABSTRACT:** Existing pollen datasets from northern Africa stored in the African Pollen Database were used to assess changes in landscape physiognomy at the end of the African Humid Period (AHP) from 5000 cal yr BP to the present using arboreal pollen percentages. The thirty-six sites available were used to map changes in arboreal cover at a sub-continental scale. Based on their location in present-day forested and non-forested areas and their relatively higher temporal resolution eight of them were selected to examine the timing and amplitude of the vegetation response in more detail, and particularly in the Sahel. In spite of low pollen production and dispersal of many tropical plants, which lead to the under representation of most of the trees relative to their abundance in the landscape, we were able to distinguish the geographical pattern and timing of vegetation changes. The landscape response to the end of the AHP was far from homogeneous particularly in the Sahel where a clear east-west gradient of changing tree cover is indicated with the central Sahel being notably species poor. In areas where forests were well developed during the AHP, i.e. in the south and west, the establishment of the modern landscape was abrupt with a threshold crossed between 3300 and 2500 cal yr BP according to local conditions. Elsewhere in northern Africa the switch from tree (C₃) to grass (C₄) dominated landscapes occurred more gradually during the same period. This review shows that the timing of the ecosystem response at the end of the AHP was remarkably synchronous throughout northern Africa.

<footnote n="1">¹Other affiliation: *Faculté des Sciences appliquées, CUAM, Université Ibn Zohr, B.P. 8106 Agadir, Morocco*</footnote>

<footnote n="2">²Akaegbobi, I.M., Assi-Kaudjhis, C., Ballouche, A., Buchet, G., Kadomura, C., Lebamba, J., Maley, J., Marchant, R., Mariotti Lippi, M., Médus, J., Mercuri, A.M., Njokuocha, R.C., Roche, E., Salzmann, U., Schulz, E., Sowunmi, A., Tossou, M., Vincens, A.</footnote>
## 6.1 INTRODUCTION

Reconstructing vegetation changes in tropical North Africa during the Holocene and understanding how the landscape has evolved from a 'humid' state characterized by the development of numerous lakes and wetlands into the today's hyper-arid desert continues to be the subject of extensive research (e.g. Dallmeyer et al. 2020; Krinner et al. 2012; Lézine et al. 2011; Shanahan et al. 2015). Pollen data have been successfully used to assess biodiversity changes that occurred during the African Humid Period (AHP) (deMenocal et al. 2000) such as the penetration of tropical trees into the Sahara and the Sahel at its onset or their retreat at its termination (e.g. Hély et al. 2014 and references therein). Pollen data are however extremely complex and changes in plant cover and related land-surface albedo remain difficult to be quantified. A large part of this complexity is due to the uneven geographical distribution of the data, difficulties in establishing robust chronologies, and the incomplete and/or discontinuous nature of the sedimentary series (Watrin et al. 2009). The desiccation of the ancient Saharan lakes and the deflation of exposed lacustrine deposits, still continuing today, have eroded lake sediments and considerably hampered the preservation of pollen grains. Therefore, preserved sediments provide limited time windows mainly concentrated in wettest periods. Only a single, continuous, sequence covering a time interval from the end of the AHP to the present is available for the entire Sahara (Lézine et al. 2011). Continuous pollen series with high temporal resolution are however more numerous to the south, from the Sahel to the Congo basin (e.g. Lézine et al. 2013a; Maley and Brenac 1998; Ngomanda et al. 2009; Salzmann et al. 2002; Vincens et al. 2010; Waller et al. 2007).

Differences in pollen production and dispersal between tropical plants means that interpretation of vegetation cover within the landscape from ancient pollen records is further complicated, especially in the driest regions. Most of the trees have a low pollen productivity, disperse pollen entomophilously, and are thus under-represented in the pollen spectra (Ritchie 1995). While the presence of tree pollen, even a single grain, may be indicative of the presence of the corresponding plants (Watrin et al., 2006), it is extremely difficult given the current state of knowledge, to quantify the importance of these trees in the landscape. Therefore, the timing and magnitude of the environmental change related to the end of the AHP remains poorly documented.

Here we use a simple index: the percentage of tree pollen (AP %) from selected high resolution pollen records from both continental and marine environments in northern Africa, from 5° to 19°N, in order to characterize the environmental change at the end of the AHP. This index is commonly used to qualitatively evaluate woody cover in temperate regions where most of the tree species are wind-pollinated. Our goal is to discuss how well this index can be applied to northern Africa, given the particularities of the pollen production and dissemination syndromes of tropical tree species.

## 6.2 ENVIRONMENTAL SETTING

The climatic features of northern Africa are related to the Atlantic monsoon circulation and the seasonal migration of the Intertropical Convergence Zone (ITCZ). In January, the monsoons' influence is confined to the periphery of the Gulf of Guinea and the northernmost areas are subject to the hot, dry continental trade winds. In July, the ITCZ reaches its northernmost position at 22°N allowing moist monsoon air to extend over north tropical Africa up to the southern fringe of the Sahara.

The progressive decrease of the monsoon influence and related rainfall on the continent is correlated with the latitudinal distribution of the vegetation. Five major floristic regions can be delineated from south to north: Guineo-Congolian forests of different types (evergreen and semi-evergreen forests) and secondary wooded grasslands (mean annual rainfall more than 1200 mm), Sahelian dry forests and wooded grasslands (1500–500 mm yr⁻¹), Sahelian wooded grasslands
<figure><img src="image_28.png" /><figcaption>**Figure 1.** Location map of the Holocene pollen sites used in this study (Table 1). In bold and italic, pollen sites detailed in the text (Figure 3). Boxes define the two sectors shown in Figure 5.</figcaption></figure>

and grasslands (500–100 mm yr⁻¹) and Saharan steppes (less than 100 mm yr⁻¹) (White 1983) (Figure 1). In addition, Afromontane forests occur in the Cameroon Volcanic Line between roughly 1800–2300 m asl (annual rainfall: 2000 mm yr⁻¹; mean temperature: 18 °C) bordered at upper elevations by Afroalpine grasslands and at lower elevations by sub-montane forests and wooded grasslands.

Along the coast, mangrove forests expand at the mouth of rivers where they benefit from both brackish waters and large muddy areas. Their optimal growth is attained under a rain forest climate but two main components expand northward along the coast of West Africa: *Rhizophora racemosa* reaches its northern limit at the mouth of the Senegal River near 16°N and *Avicennia germinans* extends up to Tidra at 19°50 N.

## 6.3 DATA USED

In this study, we use all the available Holocene pollen data from northern Africa stored in the African Pollen Database (APD) (Figure 1; Table 1). We focus on changes in landscape physiognomy, i.e. the shift from a C₃ plant dominated landscape to a C₄ plant dominated one at the end of the AHP. Therefore, pollen records from equatorial lowland forests (e.g. Elenga *et al.* 1994, 1996; Reynaud-Farrera *et al.* 1996) were excluded, since the impact of the environmental crisis, which occurred at the end of the AHP in the Congo Basin, was more a change in forest composition and density than the replacement of lowland forests by grasslands or wooded grasslands (Vincens *et al.* 1999). The dataset consists of 36 sites among which seven continental (Bambili, Mbalang, Diogo, Mboro-Baobab, Kajemarum, Jikaryia, Yoa) and one marine (GeoB 9503-5) pollen records have been selected in order to characterize the evolution of the landscape in the
<table><caption>**Table 1.** List of the pollen sites used in this study according to latitude from north to south in the two sectors defined in this study. In bold and italic = selected sites, see black dots on Figure 1.</caption><thead><tr><th>Site name</th><th>Latitude</th><th>Longitude</th><th>Altitude (m asl)</th><th>Country</th><th>Time frame (cal yr BP)</th><th>Reference</th></tr></thead><tbody><tr><td colspan="7" style="text-align: center; font-weight: bold;">Central sector</td></tr><tr><td>SETTAFET</td><td>25.35</td><td>11.43</td><td>1100</td><td>Libya</td><td>5000</td><td>Schulz (1980)</td></tr><tr><td>UAN TABU [UTB]</td><td>24.86</td><td>10.52</td><td>915</td><td>Libya</td><td>4000-4250</td><td>Mercuri, and Grandi (2001)</td></tr><tr><td>UAN MUHUGGIAG [UMH]</td><td>24.84</td><td>10.51</td><td>915</td><td>Libya</td><td>4000-4250</td><td>Mercuri et al. (1998)</td></tr><tr><td><u>YOA</u></td><td>19.03</td><td>20.31</td><td>380</td><td>Chad</td><td>0-5000</td><td>Lézine et al. (2011)</td></tr><tr><td>OURSI</td><td>14.65</td><td>-0.49</td><td>290</td><td>Burkina Faso</td><td>0-3500</td><td>Ballouche and Neumann (1995)</td></tr><tr><td>KISSI</td><td>14.62</td><td>-0.14</td><td>280</td><td>Burkina Faso</td><td>500-750</td><td>Ballouche (1997)</td></tr><tr><td>TJERI</td><td>13.73</td><td>16.50</td><td>275</td><td>Chad</td><td>500-4750</td><td>Maley (2004)</td></tr><tr><td><u>JIKARYIA</u></td><td>13.31</td><td>11.08</td><td>343</td><td>Nigeria</td><td>0-5000</td><td>Waller et al. (2007)</td></tr><tr><td>BAL</td><td>13.30</td><td>10.94</td><td>300</td><td>Nigeria</td><td>250-5000</td><td>Salzmann and Waller (1998)</td></tr><tr><td><u>KAJEMARUM</u></td><td>13.30</td><td>11.02</td><td>300</td><td>Nigeria</td><td>2750-5000</td><td>Salzmann and Waller (1998)</td></tr><tr><td>KAIGAMA</td><td>13.25</td><td>11.57</td><td>330</td><td>Nigeria</td><td>3500-5000</td><td>Salzmann and Waller (1998)</td></tr><tr><td>KULUWU</td><td>13.22</td><td>11.55</td><td>330</td><td>Nigeria</td><td>4750-5000</td><td>Salzmann and Waller (1998)</td></tr><tr><td>MOWO</td><td>10.60</td><td>13.99</td><td>574</td><td>Cameroon</td><td>500-750</td><td>Delneuf and Médus (1997)</td></tr><tr><td>TILLA</td><td>10.39</td><td>12.12</td><td>690</td><td>Nigeria</td><td>0-5000</td><td>Salzmann et al. (2002)</td></tr><tr><td>GROMOUI</td><td>10.32</td><td>14.32</td><td>430</td><td>Cameroon</td><td>1000-1250</td><td>Delneuf and Médus (1997)</td></tr><tr><td><u>MBALANG</u></td><td>7.32</td><td>13.73</td><td>1110</td><td>Cameroon</td><td>0-5000</td><td>Vincens et al. (2010)</td></tr><tr><td>TIZONG</td><td>7.25</td><td>13.58</td><td>1160</td><td>Cameroon</td><td>0-4000</td><td>Lebamba et al. (2016)</td></tr><tr><td>LAC SELE</td><td>7.15</td><td>2.43</td><td>11</td><td>Benin</td><td>0-5000</td><td>Salzmann and Hoelzmann (2005)</td></tr><tr><td>OBAYI</td><td>6.82</td><td>7.37</td><td>550</td><td>Nigeria</td><td>1750-2000</td><td>Njokuocha (2012)</td></tr><tr><td>OHE POND</td><td>6.80</td><td>7.37</td><td>1502</td><td>Nigeria</td><td>1250-1500</td><td>Njokuocha and Akaegbobi (2014)</td></tr></tbody></table>

(Continued)
<table><caption>**Table 1. Continued.**</caption><thead><tr><th>Site name</th><th>Latitude</th><th>Longitude</th><th>Altitude (m asl)</th><th>Country</th><th>Time frame (cal yr BP)</th><th>Reference</th></tr></thead><tbody><tr><td>DANGBO</td><td>6.60</td><td>2.59</td><td>40</td><td>Benin</td><td>0–5000</td><td>Tossou (2002)</td></tr><tr><td>YÉVIÉDIÉ</td><td>6.53</td><td>2.37</td><td>53</td><td>Benin</td><td>1250–5000</td><td>Tossou (2002)</td></tr><tr><td>GOHO</td><td>6.44</td><td>2.57</td><td>35</td><td>Benin</td><td>750–4750</td><td>Tossou (2002)</td></tr><tr><td>MBI</td><td>6.08</td><td>10.35</td><td>2018</td><td>Cameroon</td><td>0–5000</td><td>Lézine et al. (2021)</td></tr><tr><td><u>BAMBILI 1</u></td><td>5.94</td><td>10.24</td><td>2273</td><td>Cameroon</td><td>0–5000</td><td>Lézine et al. (2013a)</td></tr><tr><td>NIGER DELTA [DC2]</td><td>4.55</td><td>6.43</td><td>0</td><td>Nigeria</td><td>500–3750</td><td>Sowunmi (1981)</td></tr><tr><td colspan="7" style="text-align: center; font-weight: bold;">Western sector</td></tr><tr><td>BAIE SAINT JEAN [BSJ]</td><td>19.47</td><td>−16.30</td><td>1</td><td>Mauritania</td><td>1750–3750</td><td>Unpublished (Lézine A.M.)</td></tr><tr><td>TIGUENT</td><td>17.25</td><td>−16.02</td><td>8</td><td>Mauritania</td><td>3000–3250</td><td>Médus and Barbey (1979)</td></tr><tr><td><u>GeoB 9503-5</u></td><td>16.07</td><td>−16.65</td><td>−50</td><td>Atlantic Ocean</td><td>1500–4250</td><td>Bouimetharhan et al. (2009)</td></tr><tr><td>ST LOUIS</td><td>16.03</td><td>−16.48</td><td>2</td><td>Senegal</td><td>0–1000</td><td>Fofana et al. (2020)</td></tr><tr><td>POTOU</td><td>15.75</td><td>−16.50</td><td>11</td><td>Senegal</td><td>0–5000</td><td>Lézine (1988)</td></tr><tr><td>OGO [OS2]</td><td>15.57</td><td>−13.28</td><td>15</td><td>Senegal</td><td>750–1000</td><td>Feller et al. (1981)</td></tr><tr><td>LOMPOUL</td><td>15.42</td><td>−16.72</td><td>3</td><td>Senegal</td><td>2000–5000</td><td>Lézine (1988)</td></tr><tr><td><u>DIOGO 2</u></td><td>15.27</td><td>−16.80</td><td>8</td><td>Senegal</td><td>250–5000</td><td>Lézine (1988)</td></tr><tr><td>TOUBA N'DIAYE 2 [TND2]</td><td>15.17</td><td>−16.87</td><td>6</td><td>Senegal</td><td>1000–5000</td><td>Lézine (1988)</td></tr><tr><td><u>MBORO-BAOBAB</u></td><td>15.15</td><td>−16.91</td><td>4</td><td>Senegal</td><td>0–4500</td><td>Lemonnier and Lézine (this volume)</td></tr></tbody></table>

two main vegetation types which expanded in northern Africa during the AHP: (i) continuous forests in the Cameroon Highlands, and (ii) gallery forests around water bodies in the Sahara and Sahel within a dry, open regional environment. The whole dataset was then used to map landscape changes at a sub-continental scale.

The chronology is given in calendar years BP (cal yr BP) after conversion of ¹⁴C dates to calendar age according to Stuiver *et al.* (2020). The age models were retrieved from the published articles or from the APD (i.e. based on linear interpolation between the dated samples) taking into account possible discontinuities in sediment deposition. Arboreal pollen types (AP) include trees, shrubs, palms and lianas. Undifferentiated pollen types (UP) include taxa corresponding to plants with various life forms (trees, shrubs, lianas or herbs) and taxa determined at a low taxonomic level, typically the family level (Vincens *et al.* 2007). Percentages are calculated against a sum of total pollen excluding those of aquatics (including Cyperaceae), cultivated and Mediterranean plant types.
## 6.4 POLLINATION SYNDROMES OF THE TROPICAL PLANTS

The pollination syndromes of the families represented at the seven selected sites (Table 2) are derived from Watson and Dallwitz (1992) and the gymnosperm database (www.conifers.org). This reveals the major challenge of representing landscapes from pollen data in northern Africa. Most of the families present in our pollen records are entomophilous or zoophilous (mainly cheiropterophilous and ornithophilous), whereas 16% are anemophilous or entomophilous and only 5% are strictly anemophilous. Most of the entomophilous/zoophilous plants produce small amounts of pollen, which may be exceptionally large. As a result, they are under-represented (e.g. *Adansonia*) or rarely (e.g. *Isoberlinia*, *Daniellia*) represented in the pollen assemblages (Watrin *et al.*, 2006). In contrast, members of the Poaceae family, which is exclusively anemophilous, produce large quantities of pollen, and therefore largely dominate the pollen assemblages, particularly those derived from wooded grasslands and grasslands. Taking into account these specifications and the difficulties of measuring the quantity of pollen grains produced by the plants, the most widely used method for describing the pollen signature of the modern vegetation in terms of diversity, biomes or vegetation types is that of surface samples, either from soil, mosses or pollen traps. This method has been successfully developed in tropical Africa since Hedberg (1954). Gajewski *et al.* (2002) have validated the APD dataset, which covers all of sub-Saharan Africa.

## 6.5 POLLEN REPRESENTATION OF THE MODERN LANDSCAPE

In northern Africa the pollen-plant and pollen-biome relationships have been extensively studied (e.g. Lézine et al. 2009; Watrin et al. 2007 and references therein). These studies have identified the pollen signature of common plants and biomes along latitudinal (Lézine et al. 2009) or altitudinal gradients (Verlhac et al. 2018) in order to provide the basis for reliable vegetation reconstructions in the past and for quantitative estimates of climate parameters from pollen data. However, the physiognomy of the vegetation is only rarely addressed (Lézine and Hooghiemstra 1990; Vincens et al. 2000). Based on arboreal pollen percentages (AP%) and undifferentiated pollen percentages (UP%), Figure 2A shows that the two extreme vegetation types along a south-north transect in northern Africa, the Guineo-Congolian forest in the south and the desert steppe in the north, are easily identified (Lézine and Hooghiemstra 1990). The Guineo-Congolian forest is represented by AP higher than 80% and UP lower than 8% while the desert steppe is represented by AP lower than 10%. In desert steppe, UP (mainly herbs, sub-shrubs or shrubs from the Amaranthaceae, Brassicaceae, Caryophyllaceae, Asteraceae families) values are exceptionally high, representing more than 50%. While AP% consistently range between 20% and 50% in the Sudanian dry forests of southern Senegal, they strongly vary between 5 and 35% in the Sahelian woodlands and wooded grasslands, making the pollen signature of the tree cover in these grass-dominated landscapes difficult to detect. The difficulty in detecting tree cover is mainly due to the uneven distribution of the trees within the landscape. This is particularly the case in the transition zone between forest and desert where trees are mostly concentrated along rivers and wetlands (Trochain 1940; White 1983). In addition, these vegetation formations share numerous tree species, the distribution of which is denser in the woodlands and sparser in the wooded grasslands (e.g. Combretaceae, *Acacia*). The characteristics of their pollen production and dispersal hampers any reliable reconstruction of vegetation types.

In the Equatorial regions, the forest-wooded grassland transect of Kandara (Vincens et al. 2000) shows AP higher than 60% in the forest. AP dramatically decrease to less than 10% in the adjacent wooded grassland and the transition between the two is typified by intermediate values (45%) (Figure 2B). However, as stated by the authors, the different kind of forests (*Albizia* forest and *Rinorea* forest) cannot be distinguished, and no decrease in AP% is observed in the forest
<table><caption>**Table 2.** List of the families encountered in the Holocene pollen sites used in this study (Table 1) and included in the pollen sum with their pollination syndromes (after Watson and Dallwitz (1992) and the gymnosperm database (www.conifers.org)).</caption><thead><tr><th>Family</th><th>Pollination system</th><th>Family</th><th>Pollination system</th></tr></thead><tbody><tr><td>Acanthaceae</td><td>entomophilous</td><td>Liliaceae</td><td>entomophilous</td></tr><tr><td>Aizoaceae</td><td>entomophilous</td><td>Lobeliaceae</td><td>entomophilous</td></tr><tr><td>Alangiaceae</td><td>entomophilous</td><td>Loganiaceae</td><td>entomophilous</td></tr><tr><td>Amaranthaceae</td><td>entomophilous</td><td>Loranthaceae</td><td>entomophilous, or ornithophilous</td></tr><tr><td>Anacardiaceae</td><td>entomophilous</td><td>Lythraceae</td><td>entomophilous</td></tr><tr><td>Annonaceae</td><td>entomophilous</td><td>Malpighiaceae</td><td>entomophilous</td></tr><tr><td>Apiaceae</td><td>entomophilous</td><td>Malvaceae</td><td>entomophilous</td></tr><tr><td>Apocynaceae</td><td>entomophilous</td><td>Melastomataceae</td><td>entomophilous, or ornithophilous, or cheiropterophilous</td></tr><tr><td>Aquifoliaceae</td><td>entomophilous</td><td>Meliaceae</td><td>entomophilous (usually)</td></tr><tr><td>Araliaceae</td><td>entomophilous</td><td>Melianthaceae</td><td>entomophilous, or ornithophilous</td></tr><tr><td>Asclepiadaceae</td><td>entomophilous</td><td>Menispermaceae</td><td>unknown</td></tr><tr><td>Asparagaceae</td><td>entomophilous</td><td>Mimosaceae</td><td>entomophilous, or ornithophilous, or cheiropterophilous, or anemophilous</td></tr><tr><td>Asteraceae</td><td>entomophilous (mostly), or anemophilous</td><td>Moraceae</td><td>anemophilous, or entomophilous</td></tr><tr><td>Balanitaceae</td><td>entomophilous (mostly), or anemophilous</td><td>Myricaceae</td><td>anemophilous</td></tr><tr><td>Balsaminaceae</td><td>entomophilous</td><td>Myristicaceae</td><td>entomophilous</td></tr><tr><td>Begoniaceae</td><td>entomophilous</td><td>Myrsinaceae</td><td>entomophilous</td></tr><tr><td>Bignoniaceae</td><td>entomophilous, or ornithophilous, or cheiropterophilous</td><td>Myrtaceae</td><td>entomophilous, or ornithophilous</td></tr><tr><td>Bombacaceae</td><td>cheiropterophilous</td><td>Nyctagynaceae</td><td>entomophilous</td></tr><tr><td>Boraginaceae</td><td>entomophilous</td><td>Ochnaceae</td><td>entomophilous</td></tr><tr><td>Brassicaceae</td><td>anemophilous, or entomophilous</td><td>Olacaceae</td><td>entomophilous</td></tr><tr><td>Buddleyaceae</td><td>entomophilous, or ornithophilous</td><td>Oleaceae</td><td>anemophilous (mostly), or entomophilous</td></tr><tr><td>Burseraceae</td><td>entomophilous</td><td>Orobanchaceae</td><td>entomophilous</td></tr><tr><td>Caesalpiniaceae</td><td>entomophilous;</td><td>Palmae</td><td>entomophilous (mostly), or anemophilous</td></tr><tr><td>Campanulaceae</td><td>entomophilous</td><td>Pandanaceae</td><td>anemophilous (mostly), or entomophilous, or ornithophilous, or cheiropterophilous</td></tr><tr><td>Capparidaceae</td><td>entomophilous</td><td>Passifloraceae</td><td>entomophilous</td></tr></tbody></table>

(Continued)
<table><caption>**Table 2. Continued.**</caption><thead><tr><th>Family</th><th>Pollination system</th><th>Family</th><th>Pollination system</th></tr></thead><tbody><tr><td>Caryophyllaceae</td><td>entomophilous</td><td>Phyllanthaceae</td><td>entomophilous</td></tr><tr><td>Casuarinaceae</td><td>anemophilous</td><td>Plantaginaceae</td><td>anemophilous, or anemophilous and entomophilous</td></tr><tr><td>Celastraceae</td><td>entomophilous</td><td>Poaceae</td><td>anemophilous (exclusively)</td></tr><tr><td>Chrysobalanaceae</td><td>entomophilous, or cheiropterophilous</td><td>Podocarpaceae</td><td>anemophilous</td></tr><tr><td>Clusiaceae</td><td>entomophilous, or ornithophilous</td><td>Polygalaceae</td><td>entomophilous</td></tr><tr><td>Cochlospermaceae</td><td>entomophilous</td><td>Polygonaceae</td><td>anemophilous, or entomophilous</td></tr><tr><td>Combretaceae</td><td>entomophilous, or ornithophilous</td><td>Primulaceae</td><td>entomophilous</td></tr><tr><td>Commelinaceae</td><td>entomophilous</td><td>Proteaceae</td><td>entomophilous, or ornithophilous, or cheiropterophilous (?), or by unusual means (notably by small marsupials and rodents)</td></tr><tr><td>Connaraceae</td><td>autogamous or entomophilous</td><td>Ranunculaceae</td><td>anemophilous, or entomophilous</td></tr><tr><td>Convolvulaceae</td><td>entomophilous</td><td>Resedaceae</td><td>entomophilous</td></tr><tr><td>Crassulaceae</td><td>entomophilous</td><td>Rhamnaceae</td><td>entomophilous</td></tr><tr><td>Cucurbitaceae</td><td>entomophilous</td><td>Rhizophoraceae</td><td>anemophilous, or entomophilous</td></tr><tr><td>Cupressaceae</td><td>anemophilous</td><td>Rosaceae</td><td>anemophilous (occasionally), or entomophilous (usually)</td></tr><tr><td>Dichapetalaceae</td><td>entomophilous</td><td>Rubiaceae</td><td>entomophilous</td></tr><tr><td>Dilleniaceae</td><td>entomophilous</td><td>Rutaceae</td><td>entomophilous</td></tr><tr><td>Dioscoreaceae</td><td>entomophilous</td><td>Salicaceae</td><td>anemophilous, or entomophilous</td></tr><tr><td>Dipsacaceae</td><td>entomophilous</td><td>Salvadoraceae</td><td>entomophilous</td></tr><tr><td>Ebenaceae</td><td>entomophilous</td><td>Sapindaceae</td><td>entomophilous</td></tr><tr><td>Ephedraceae</td><td>anemophilous, or entomophilous</td><td>Sapotaceae</td><td>entomophilous</td></tr><tr><td>Ericaceae</td><td>entomophilous (usually?)</td><td>Scrophulariaceae</td><td>entomophilous, or ornithophilous</td></tr><tr><td>Euphorbiaceae</td><td>entomophilous</td><td>Simaroubaceae</td><td>entomophilous, or ornithophilous</td></tr><tr><td>Fabaceae</td><td>entomophilous, or ornithophilous, or cheiropterophilous</td><td>Solanaceae</td><td>entomophilous</td></tr><tr><td>Flacourtiaceae</td><td>entomophilous</td><td>Sphenocleaceae</td><td>entomophilous</td></tr><tr><td>Gentianaceae</td><td>entomophilous</td><td>Sterculiaceae</td><td>entomophilous</td></tr></tbody></table>

(Continued)
<table><caption>**Table 2. Continued.**</caption><thead><tr><th>Family</th><th>Pollination system</th><th>Family</th><th>Pollination system</th></tr></thead><tbody><tr><td>Geraniaceae</td><td>entomophilous</td><td>Tamaricaceae</td><td>entomophilous, or anemophilous</td></tr><tr><td>Gesneriaceae</td><td>entomophilous, or ornithophilous, or cheiropterophilous</td><td>Thymeleaceae</td><td>entomophilous</td></tr><tr><td>Hippocrateaceae</td><td>entomophilous</td><td>Tiliaceae</td><td>entomophilous</td></tr><tr><td>Hymenocardiaceae</td><td>entomophilous (mostly), or anemophilous</td><td>Tribulaceae</td><td>entomophilous</td></tr><tr><td>Hypericaceae</td><td>entomophilous</td><td>Ulmaceae</td><td>entomophilous</td></tr><tr><td>Icacinaceae</td><td>entomophilous</td><td>Urticaceae</td><td>anemophilous</td></tr><tr><td>Irvingiaceae</td><td>entomophilous</td><td>Verbenaceae</td><td>entomophilous</td></tr><tr><td>Lamiaceae</td><td>entomophilous or ornithophilous</td><td>Vitaceae</td><td>entomophilous (mostly), or anemophilous</td></tr><tr><td>Lecythidaceae</td><td>entomophilous</td><td>Zygophyllaceae</td><td>entomophilous</td></tr><tr><td>Portulaceae</td><td>entomophilous</td><td></td><td></td></tr></tbody></table>

<figure><img src="image_29.png" /><figcaption>**Figure 2.** Modern pollen deposition in three different sectors of northern Africa: (A): a South-North transect in Senegal-Mauritania-Algeria (Lézine and Hooghiemstra 1990), (B): the Kandara forest-savanna transect in Southern Cameroon (Vincens *et al.* 2000), and (C): an altitudinal transect in the Cameroon highlands (Verlhac *et al.* 2018). Percentages calculated against a sum excluding fern spores, aquatics and Cyperaceae pollen. Dark grey: AP%. Light grey: UP%.</figcaption></figure>
<figure><img src="image_30.png" /><figcaption>**Figure 3.** Percentages of Arboreal (AP) and Undifferentiated pollen types (UP) in selected sites from northern Africa from 5000 cal yr BP to the present. In order to facilitate the comparison between sites, data are averaged by 250-years' time bins.</figcaption></figure>

gaps linked to recent settlements. A slightly different pattern is observed in the montane forests Cameroon (Figure 2C; Verlhac *et al.* 2018). As expected, AP reach high values, up to 90%, within the forest. However, they strongly vary, reflecting the highly heterogeneous forest cover (Momo Solefack 2009) (Figure 2C). This is particularly the case at higher elevations where the trees are irregularly distributed and the upper tree line is often patchy due to marked topography. Afroalpine grasslands at the top of the mountains and wooded grasslands below the forest block show AP averaging 15% and 10%, respectively.

## 6.6 THE HOLOCENE POLLEN SEQUENCES

Vincens *et al.* (1999) first reviewed the equatorial forest response at the end of the AHP. They showed that the lowland forests changed in nature from rain or swamp forests to woodlands or secondary forests characterized by an increase in light demanding trees. While the timing of this change is remarkably coherent in the lowlands of Cameroon at around 2400 cal yr BP (Lézine *et al.* 2013b and reference therein), it varies in Congo within a time interval from 3800 and 1800 cal yr BP according to local hydrological conditions (Vincens *et al.* 1999). In mountain areas, a clear signal of forest disruption occurred at 3300–3000 cal yr BP (Figure 3): AP values abruptly fell from 50 to 9% in the Adamawa plateaus (Mbalang) and then remained below 11% up to the present day. At higher elevations (Bambili), AP decreases from 84% to 54% at 3300 cal yr
<figure><img src="image_31.png" /><figcaption>**Figure 4.** Arboreal pollen percentage (AP%) and undifferentiated pollen percentage (UP%) from selected sites from the Sahara and the Sahel. Dashed lines show the second order running average.</figcaption></figure>

BP and then remained at this level up to 2500 cal yr BP. AP subsequently increased again to a maximum of 65% indicating a later forested phase, albeit less developed compared to that of the AHP. This second phase of forest development ended during the last millennium.

In the Sahel, the pollen diagrams testify to a contrasting situation: in the west, near the Atlantic coast, AP% were remarkably high during the Holocene forest phase indicating dense gallery forests in the coastal region (Diogo). AP decreased from 72% to 19% between 3250 and 1250 cal yr BP through a well-marked threshold at 2500 BP characterized by a drop of about 20%. In the same region however, Mboro-Baobab did not record such an evolution and AP values displayed rather constant percentages during the last 5000 years, only slightly fluctuating between 30 and 20%. In the central Sahel, AP never reached percentages as high as those recorded in the west, even during the AHP reflecting poorly developed gallery forests around water bodies. The maximum of AP at Kajemarum and Jikaryia in the Manga region of northern Nigeria did not exceed 26% and 19%, respectively. At Kajemarum, AP definitively disappeared at 3000 cal yr BP. At Jikaryia, the transition between the Holocene and the present landscape was less contrasted though a slight decrease in AP% was observed at the same time. At the Sahara/Sahel transition (Yoa, GeoB 95013-5) AP were constantly less than 23% during the AHP. At Yoa, the retreat of tropical plant species (e.g. *Celtis*, *Piliostigma*, *Grewia*) and the establishment of desert conditions at the end of the AHP occurred in two phases at 4700 and 2700 cal yr BP, respectively (Lézine *et al.* 2011). This transition occurred in a context of poorly developed tree cover and is therefore not reflected by our AP index. Interestingly, AP% slightly increased during the last few centuries which may reflect increased anthropogenic influence, for instance the establishment of palm tree plantations at Yoa (Lézine *et al.* 2011), or the occurrence of episodic humid events in the Senegal River Basin (Bouimetarhan *et al.* 2009). In order to refine the timing and structure of the end of the AHP in the Sahel, we plotted the undifferentiated pollen types (UP) (Figure 4) that are especially abundant in the most arid regions as shown in the modern samples (Figure 2). Three sectors of the Sahara and the Sahel emerge from the examination of UP %: at the Sahara/Sahel boundary, the UP % gradually increased from 5000 cal yr BP (or even before) to the present with a peak at 2700 cal yr BP. A roughly similar trend is observed in the Central Sahel. Here they were present from 4000 cal yr BP and then remained constant throughout the last millennia. In contrast, UP % increased much later, since 2700 cal yr BP in the western Sahel.

## 6.7 DISCUSSION

Our study illustrates one of the major problems of tropical palynology: can the abundance of trees and grasses in the landscape be described using a simple index: the percentage of arboreal
pollen? Open landscapes dominate in Africa today between 30°S and 30°N with the exception of the equatorial mangrove, and from montane forests. These open landscapes are of various types, ranging from dry forests, to woodlands, wooded grasslands and grasslands (White 1983). The particularities of pollen production and dispersal of tropical plants mean that trees are often under-represented in pollen spectra, making distinction between these types of vegetation difficult. Based on the modern samples (Figure 2), we have considered three AP% categories to characterize the late Holocene landscape of northern Africa (Figures 5 and 6): (i) AP higher than 45% corresponding to a dense tree cover, (ii) AP lower than 15% indicating grass-dominated landscapes, and (iii) intermediate values ($15 < AP < 45\%$), secondary/dry forests. Figure 5 shows that dense forest stands remained developed in mangroves along the coast of the Gulf of Guinea, in the western Sahel and in the Cameroon highlands well after the establishment of xeric conditions at the end of the AHP. Surprisingly, it suggests that there was no transition from forested to open landscapes from south to north throughout northern Africa with open landscapes dominating largely from 5000 to c. 3000 cal yr BP north of 10°N. The absence of intermediate tree cover between forests and open landscapes is likely an artefact due to the difficulties evoked in distinguishing woodlands from wooded grasslands and grasslands. While different kinds of open environments are difficult to infer from AP%, it is even more difficult to derive related climatic factors. For instance, modern AP% are higher at Yoa in the Saharan steppe, where the annual rainfall does not exceed 7 mm (23%) than at Mbalang in the Sudanian wooded grassland, where it averages 1500–1600 mm (6.5%). Environmental reconstructions in such grass-dominated landscapes are thus particularly challenging and new methodological approaches such as those developed by Sugita (2007) are crucial for a better estimation of regional vegetation proportions (See Gaillard et al., this volume). Despite this major limitation and the purely qualitative aspect of our approach, two key results emerge from our review (6.7.1 and following).

## 6.7.1 Abrupt forest collapses or gradual establishment of xeric conditions?

In densely forested areas from western Sahel (Diogo) and the Cameroon Highlands (Bambili, Mbalang), AP% permits identification of the tipping points between forested and non-forested (or less-forested) states that occurred at times, varying according to altitude and hydrological conditions, between 3300 and 2500 cal yr BP (Figure 3). However, the determination is only qualitative since the evaluation of its magnitude depends mainly on the pollen productivity and dispersion of tropical trees (see Gaillard et al., this volume). Abrupt forest collapse most certainly originated from the middle Holocene, when an increased seasonality in rainfall was established (Vincens et al. 2010). At Bambili, the progressive destabilization of the forest is thought to have originated from the ‘8.2 event’, which could thus be considered as the ‘early warning signal’ (Lenton 2011) of the environmental crisis that took place several millennia later, at 3300 cal yr BP (Lézine et al. 2013a). Unlike these sites, where a threshold was abruptly crossed leading to the collapse of the forests, the establishment of an open landscape at the end of the AHP was gradual (Figure 4); tree cover decreased gradually in already arid areas, particularly in the central Sahel. This supports the interpretations by Kröpelin et al. (2008) that the transition to xeric conditions at the end of the AHP was a gradual one. Consequently, pollen data from the Sahel do not support the earlier hypotheses of an abrupt environmental change at the end of the AHP as proposed by de Menocal et al. (2000).

## 6.7.2 A complex pattern of environmental change

Changes in distribution of trees across the landscape was not merely latitudinal following a south-north gradient of decreasing precipitation (Figure 5). The most striking feature is the difference between the central and western Sahel. We therefore consider two separate transects, one along the west coast and the other in central northern Africa. Forests widely developed in the west.
<figure><img src="image_32.png" /></figure>

<figure><img src="image_33.png" /><figcaption>**Figure 5.** (A) Spatial distribution of tree pollen percentages from 5000 cal yr BP to the present in northern Africa. Three categories are considered with AP > 45% showing dense tree cover, 15 < AP < 45% intermediate tree cover and AP < 15% sparse tree cover. (B) Patterns of tree cover change according to latitude in the two sectors defined in Figure 1. The selected sites are indicated on the left column by a box.</figcaption></figure>
<figure><img src="image_34.png" /><figcaption>**Figure 6.** Timing of landscape change in the western (on the left) and central (on the right) sectors of northern Africa. The curves show the number of sites in the categories defined by AP% in northern Africa (AP = 0, AP < 15%, 15 < AP < 45%, >45%). Data are expressed in per cent of the total of sites present in each time bin (cf. Figure 5B).</figcaption></figure>

Their expansion reached approximately 16°N, i.e. the mouth of the Senegal River. In contrast, forests only occurred along the coast and in the highlands in central Africa. Trees were rare north of 10°N in the Sahel, except during a time interval spanning from 4500 to 3500 cal yr BP in the Manga region (13°N) and in the central Saharan massifs in southern Libya (25°N) where they slightly increased (Figures 5 and 6).

Despite the limited number of sites in both sectors clear patterns can be discerned. In the western sector, the major change in forest cover occurred from 3000 to 2250 cal yr BP. This is shown by the opposing trends between the number of sites with AP values above 45%, which were gradually decreasing in number and those with AP values ranging from 15 to 45%, which were gradually increasing. Sparse tree cover became gradually commoner over the western sector from 4250 cal yr BP with the modern landscape composed of woodlands and wooded grasslands being definitively established after 1750 cal yr BP. Unlike the western sector, sites with sparse tree cover dominated the central sector throughout the last 5000 years. The number of such sites progressively increased in two phases respectively dated 3500 and 1500 cal yr BP. Sites with
dense tree cover were restricted to the Cameroon Highlands and the mangrove areas along the Gulf of Guinea. In both sectors, they declined from 1500 cal yr BP onwards. The most striking result of our study is the behaviour of sites with intermediate tree cover. As already noted, trees increased in the Manga sector of the Sahel around 3800 cal yr BP due to the recovery of tropical taxa during a short wet phase (Waller *et al.* 2007). After 3500 cal yr BP, trees disappeared from the Manga sector. Elsewhere in the central sector of northern Africa, the number of sites with intermediate and sparse tree cover increased from 2250 cal yr BP onwards.

## 6.8 CONCLUSIONS

Reconstructing vegetation cover from AP% is highly challenging, particularly given the predominantly open vegetation types that are widely distributed in northern Africa from the Sudanian dry forests to the Sahelian wooded grasslands and Saharan grasslands. Despite this caveat, our review shows that the landscape response to the end of the AHP was far from homogeneous particularly in the Sahel where a clear east-west gradient of tree cover change is indicated, the central Sahel being notably poor in tree species as shown for instance in the Lake Chad (Tjeri) and the Niger bend (Oursi, Kissi) areas. In areas where forests were well developed during the AHP, i.e. in the south and west, the establishment of the modern landscape was abrupt with a threshold crossed between 3300 and 2500 cal yr BP according to local conditions. Elsewhere in northern Africa the switch from tree ($C_3$) to grass ($C_4$) dominated landscapes occurred at approximately the same time, but more gradually. This review allows the timing of the ecosystem response at the end of the AHP be identified, which was remarkably synchronous throughout northern Africa, in contrast to hydrological data, which suggest a time transgressive end to the AHP (Shanahan *et al.* 2015).

## ACKNOWLEDGEMENTS

This work contributes to the ACCEDE ANR Belmont Forum project ((18 BELM 0001 05). Thanks are due to M.J. Gaillard (Kalmar University, Sweden) for constructive comments on the manuscript and the African Pollen Database for data access. AML and KL are funded by CNRS, LD by the University of Bremen and IB by the BMF grant PMARS2015-100.

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# Reconstructing vegetation history of the Olorgesailie Basin during the Middle to Late Pleistocene using phytolith data

Rahab N. Kinyanjui<fnref n="1" />

*Department of Earth Sciences, National Museums of Kenya, Nairobi, Kenya*

Michael Meadows<fnref n="2" />

*Department of Environmental and Geographical Science, University of Cape Town, Rondebosch, South Africa*

Lindsey Gillson

*Plant Conservation Unit, Botany Department, University of Cape Town, Rondebosch, South Africa*

Marion. K. Bamford

*The Evolutionary Studies Institute, University of the Witwatersrand, Johannesburg, South Africa*

Anna K. Behrensmeyer

*Department of Paleobiology, Smithsonian Institution, Washington, DC USA*

Richard Potts

*Human Origins Program, Smithsonian Institution, Washington, DC USA*

**ABSTRACT:** The Olorgesailie basin, located in the East African Rift System (EARS), southern Kenya (1.5–1.6°S, 36.4–36.5°E, 940–1040 m asl), is an important site for palaeoanthropological, palaeontological and geological research, with sediments dating back more than 1 Ma. Little is known about the palaeovegetation and palaeoenvironmental context of this important site and how this varied through space and time. Here we use phytolith data to reconstruct the vegetation history through the Middle and Late Pleistocene (c. 670 ka to c. 64 ka). The analysis of 24 samples from

<footnote n="1">¹Other affiliation: *Department of Environmental & Geographical Science, University of Cape Town, South Africa; School of Geographical Sciences, East China Normal University, Shanghai, China; and College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, China*</footnote>

<footnote n="2">²Other affiliation: *School of Geographic Sciences, East China Normal University, Shanghai, China; and College of Geography and Environmental Sciences, Zhejiang Normal University, China*</footnote>
palaeosols within the Olorgesailie and Oltulelei Formations uses diagnostic phytoliths to plot relative phytolith abundance diagrams documenting temporal and spatial vegetation variations. We use three phytolith indices (climate index, aridity index and tree density index) to estimate temperature, precipitation, and vegetation structure from sediments that are well-constrained chronologically by $^{40}$Ar/$^{39}$Ar dating. Spatial vegetation variation is captured through examining phytoliths from three distinct localities (Loc. OLT, Loc. B and Loc. G) over a distance of about 5 km. Results suggest that local vegetation changes approximately correspond with stratigraphic units. Phytolith indices reflect warm and moist conditions c. 670 ka, with cool and dry conditions from c. 650 ka during which time riparian and a variety of other habitats were present. An unconformity, which extends over c. 180,000 years (500 to 320 ka), is interpreted as largely caused by tectonic processes coupled with precipitation variability. A shift from woody vegetation to C₄ grasslands is evident following the unconformity, and riparian habitats were again present. Considerable climate variability is apparent thereafter, with inconsistent precipitation conditions until c. 220 ka when more stable and moist conditions set in until c. 64 ka. The study documents vegetation dynamics directly associated with the Middle to Late Pleistocene palaeontological and archaeological record of Olorgesailie.

## 7.1 INTRODUCTION

East Africa is well known for its archive of human evolutionary history and the long-term history of ecological interactions between faunal and floral species and their environments (Bobe and Behrensmeyer 2002; Potts 1998). Tectonic processes created the episodic fossilization and preservation of records of ancient life in the East Africa Rift system (EARS) (Brown and Feibel 1991; Feibel 1999; Campsiano and Feibel 2008). Extensively collected and documented EARS fossils have addressed a variety of research questions including human and faunal evolutionary history, extinction and speciation events, species-environment interactions and the impact of climate change on past ecosystems (Bobe and Behrensmeyer 2004; deMenocal 2004; Feakins et al. 2007; Lepre et al. 2007; Potts and Faith 2015; Trauth et al. 2007).

Previous studies suggest that African climate and vegetation cover have been highly variable since the early Pliocene, oscillating from warm and humid to cool and dry episodes that can be correlated with orbital oscillations (Cerling et al. 2011; deMenocal 1995; Feakins et al. 2007; Lepre et al. 2007; Potts 2013; Trauth et al. 2007). These oscillations resulted in habitats that varied between woodland, wooded grassland and open grassland. Such vegetation dynamics influenced hominin diets and ecomorphology in the region, such as in the Awash and Olduvai basins (Albert et al. 2009; Ashley et al. 2010a; Bamford et al. 2006; Basell 2007; Cerling et al. 2010; White et al. 2010; WoldeGabriel et al. 2009).

In the Olorgesailie basin, vegetation cover has previously been reconstructed in only a single palaeosol dated c. 1 Ma, based on carbon isotope data and faunal remains (Sikes et al. 1999). The rich palaeontological, archaeological and geological data published from the basin have otherwise lacked a parallel body of evidence on vegetation cover and how its structure changed over time and across the landscape. Initial steps geared to reconstructing the vegetation cover and structure were hindered by poor preservation of fossil pollen and other organic plant remains due to high salinity in the basin (Livingstone and Mworia 1999). A subsequent feasibility study showed the potential for using fossil phytoliths to reconstruct vegetation cover and structure during the Middle to Late Pleistocene of the basin (Kinyanjui 2012).

Phytoliths are plant silica bodies that form when silica is deposited within and around plants cells during evapotranspiration, resulting in cell casts/replicas that are morphologically distinct. The silica cells are preserved in the soils after the decomposition of the parent plants (Mulholland and Rapp 1992; Piperno 1988; 2006). They are inorganic in nature, preserve well in a variety of depositional regimes, and are particularly useful because of good preservation in
regions where organic plant remains are susceptible to oxidation and thus less likely to accumulate (Piperno 2006). Phytolith research in East Africa has gained popularity as a reliable proxy for reconstructing past vegetation cover (Alexandre *et al.* 1997; Bremond *et al.* 2005a, b; 2008; Fredlund and Tieszen 1994) geared toward understanding past environments (Albert *et al.* 2012; 2015; Bamford *et al.* 2006; Barboni *et al.* 2009; 2010; Estaban *et al.* 2020; Kinyanjui 2013). In addition, phytolith indices can be used to determine changes in precipitation, vegetation structure dynamics, and provide coarse estimates of variations in temperature through time (Aleman *et al.*, 2008; Alexandre *et al.* 1997; Bremond *et al.* 2008; Fredlund and Tieszen 1997).

This paper presents phytolith data from the upper Olorgesailie Formation dated between c. 670 ka and 500 ka (Deino et al. 2018; Isaac 1978) and the Oltulelei Formation dated between c. 320 ka to c. 36 ka (Behrensmeyer et al. 2018; Deino et al. 2018). The stratigraphic sequence covers a significant period when hominins acquired new adaptive strategies associated with changing environments, which also coincided with replacement of mega-herbivore species by smaller herbivore taxa in the basin (Potts 1998; Potts and Faith 2015; Potts et al. 2018) associated with climate and local tectonic processes (Behrensmeyer et al. 2018; Potts et al. 2020).

## 7.2 STUDY SITE: OLORGESAILIE BASIN

The Olorgesailie basin is located in the southern part of the Kenyan Rift Valley (1°3'S and 36°2'E; 940–1040 m asl) (Figure 1). It is renowned for its high concentration of Acheulean hand axes dated c. 1.2 Ma to 500 ka (Deino and Potts 1990; Isaac 1977; 1978; Potts 1989; Potts et al. 1999). The basin lies near the southern end of the Eastern Arc of the East African Rift System (EARS). To the south it is bounded by lavas associated with Mt. Olorgesailie, an extinct Pliocene-Early Pleistocene age volcano, while to the north, east and west the basin is delimited by faulted ridges of trachytes, phonolites, and basalts extruded during the Plio-Pleistocene (Baker and Mitchell 1976; Isaac 1978; Shackleton 1978). The basin's present drainage system flows from north to south following the slope of the rift floor (Baker 1958), and from east to west along the northern foothills of Mt. Olorgesailie, although tectonic movements and volcanism altered these drainage patterns in the past (Behrensmeyer et al. 2002; 2018). The main outcrops of the basin north of Mt. Olorgesailie cover an area of c. 65 km².

### 7.2.1 Present-day climate and vegetation

Climate in the Olorgesailie region is largely controlled by the annual north-south oscillation of the Intertropical Convergence Zone (ITCZ) (Hills 1978; Kenworthy 1966; Nicholson 1996) resulting in two distinct rainy seasons: (i) long rains from March to June, and (ii) short rains from October to December (Asani and Kinuthia 1979; Griffiths 1958; 1972; Nicholson 1996; Sansom 1954). There are, however, anomalies in the rainfall pattern influenced by local topography. In this regard, the southern Kenya Rift Valley receives variable mean annual rainfall, for example 1000–1500 mm in the rift-margin highlands and 250–500 mm in the rift-axis lowlands (Griffiths 1972; Mutai and Ward 2000). The mean annual rainfall around the Olorgesailie basin is less than 500 mm which, combined with an evapo-transpiration rate exceeding 2400 mm/year, results in the negative hydrological balance responsible for the semi-arid condition of the basin (Damnati and Taieb 1995).

Vegetation in the Olorgesailie basin today is classified as a semi-arid variant of *Commiphora-Acacia* bushland (White 1983) or as a Northern *Acacia-Commiphora* bushland (WWF Eco-regions) (Figure 1). The dominant woody species include *Acacia tortilis* (Forssk.) Hayne, *A. senegal* (L.) Willd., *A. mellifera* (Vahl)Benth, (Figure 2B), *Commiphora africana* (A. Rich) Engl., *C. campestris* Engl., *C. samharensis* Schweinf., *C. schimperi* (O. Berg) Engl. *Terminalia* sp., *Balanites* spp., *Grewia bicolor* Juss., *G. villosa* Willd., *Boscia coriacea* Pax, (Figure 2B)
<figure><img src="image_36.png" /><figcaption>**Figure 1.** Map showing the location of the Olorgesailie basin and WWF vegetation designated ecoregions (White 1983).</figcaption></figure>

and *Salvadora persica* L. The shrub component comprises *Sericocomopsis hildebrandtii* Schinz, *Barleria* sp., *Aerva* sp. and *Indigofera* sp. Most of the trees are deciduous and are in leaf during and after rains (Livingstone and Mworia-Maitima 1999; Mworia *et al.* 1988). Grasslands are C4-dominated, mostly Chloridoideae family such as *Chloris roxburghiana* Schult., *Dactyloctenium bogdanii* S.M Phillips, *Eragrostis cilianesis* (All.) F.T. Hubb., *Tetrapogon cenchriformis* (A. Rich.) W.D Clayton, *Sporobolus jacquemontii* Kunth. and *Brachyachne* spp. (Livingstone and Mworia-Maitima 1999; Mworia *et al.* 1988). Elements of riverine gallery forest are also present along the seasonal river channels (lagas); they include *Syzygium cordatum* Krauss, *S. guineense* (Willd.) DC., *Delonix elata* (L.) Gamble and *Terminalia* spp., while *Kyllinga alba* Nees and *K. welwitschii* are C4 sedges common in the floodplains (Livingstone and Mworia-Maitima 1999; Mworia *et al.* 1988).

### 7.2.2 Geoarchaeology

Current lithostratigraphic description distinguishes two units: the Olorgesailie and Oltulelei Formations (Behrensmeyer *et al.* 2002; 2018; Isaac 1978; Shackleton 1978), dated primarily by the single-crystal ⁴⁰Ar/³⁹Ar method (Behrensmeyer *et al.* 2018; Deino and Potts 1990; 1992; Deino *et al.* 2018; Potts *et al.* 2018).
<figure><img src="image_37.png" /><figcaption>**Figure 2.** (A) Map showing Olorgesailie basin, localities, geo-trenches (marked with star) and the basin's geology. (B) *Acacia melliferae* and *Boscia coriaceae* visible in the photograph are among the dominant woody species in the basin.</figcaption></figure>

### 7.2.2.1 Olorgesailie formation

These are deposits comprising lacustrine, wetland/swampy, fluvial and colluvial sediments forming a composite thickness of c. 80 m (Behrensmeyer *et al.* 2002). There are fourteen members (Isaac 1978; Shackleton 1978) with the base of the oldest member (Member 1) dated c. 1.2 Ma and the youngest Member (Member 14) c. 499 ka (Behrensmeyer *et al.* 2002; Deino and Potts 1990, 1992; Deino *et al.* 2018). Erosion and excavations have exposed a rich archaeological record including Acheulean stone artifacts associated with extinct mammals, butchery sites and
<figure><img src="image_38.png" /><figcaption>**Figure 3.** Schematic diagram showing lithostratigraphic/age relationship between sections.</figcaption></figure>

hominin remains of *Homo erectus* (Potts 1994; Potts et al. 1999; 2004). Stable isotope data suggest vegetation structure around 1 Ma was predominantly C₄ grasslands (Sikes et al. 1999).

### 7.2.2.2 Oltulelei formation

These are younger deposits that overlie the Olorgesailie Formation, dated between c. 320 ka and c. 36 ka (Figure 3). The sediments rest on a major erosional unconformity, representing a hiatus of c. 180,000 years (Behrensmeyer et al. 2002; 2018; Deino et al. 2018) and consist of colluvial, alluvial, freshwater and saline lake deposits preserved in a series of erosional and channel filling regimes (Behrensmeyer et al. 2002; 2007; 2018). There are three successive members; Olkesiteti (c. 320–190 ka), Oltepesi (c. 190–50 ka) and Tinga (c. 50–36 ka) (Behrensmeyer et al. 2018; Deino et al. 2018). Exposures of these sediments have yielded stone tools of Middle Stone Age (MSA) technology and vertebrate fossils (Brooks et al. 2018; Potts et al. 2018).

## 7.3 METHODS

### 7.3.1 Laboratory methods, microscopy and identification

Phytolith extraction followed Albert's (1999) protocol with additional Acid Insoluble Fraction (AIF) steps (Mercader et al. 2010). All samples reached the minimum of 250 phytoliths counted for inclusion in the analysis, of these all but three samples yielded >500 phytoliths. Phytoliths
<figure><img src="image_39.png" /><figcaption>**Figure 4.** Micro-photographs of key fossil phytolith morphotypes identified. (a) Globular granulate, (b) globular echinate (Palm phytoliths), (c) Globular echinate (d) Globular verrucate, (e) Tracheid types, (f) Blocky types, (g) Sclereid bodies, (h) Achene (sedge phytoliths), (i) Scutiform/trichome types, (j) Crenate type, (k) Bulliform types, (l) Trapeziforms, (m) rondels, (n) saddles, (o) bilobates, (p) crosses.</figcaption></figure>

were identified at 400× magnification using an Olympus BX52 light microscope. Microphotographs were taken and viewed using image processing software; Image-Pros plus 5.1 and Infinity Capture 2. Images were stored as TIFF/JPEG files.

Morphological description and classification were based on phytolith shape and size based on the International Codes for Phytolith Nomenclature (ICPN) (Madella *et al.* 2005), while additional literature was consulted for specific taxa. Grass short cell phytoliths (GSCPs) assignments were based largely on the following studies (Barboni and Bremond 2009; Bremond *et al.* 2008; Esteban *et al.* 2016; Mercader *et al.* 2010; Neumann *et al.* 2009; 2017; Novello *et al.* 2012; Piperno 2006; Rossouw 2009; Strömberg 2004; Twiss 1992; Twiss *et al.* 1969), Woody (tree and shrub) (Albert and Weiner 2001; Mercader *et al.* 2009; Neumann *et al.* 2009; Piperno 2006; Runge 1999; Strömberg 2004) and Palm phytoliths (Figures 4b) (Albert *et al.* 2009; Ashley *et al.* 2010b; Neumann *et al.* 2009), Cyperaceae morphotypes (Honaine *et al.* 2006; Ollendorf 1992; Piperno 2006; Strömberg 2004), while the non-diagnostic types (trichomes, bulliforms, elongates) followed (Albert and Weiner 2001; Mercader *et al.* 2009; Neumann *et al.* 2009; Piperno 2006; Runge 1999; Strömberg 2004) (see Table 1).
<table><caption>**Table 1.** Summary of the diagnostic morphotypes used to identify various taxa presented herein.</caption><thead><tr><th>Major Taxa</th><th>Diagnostic morphotype (s)</th><th>Morphotype description</th><th>Comparable references</th></tr></thead><tbody><tr><td>Aristidoideae</td><td><ul><li>Bilobate convex outer margin long shaft.</li></ul></td><td><ul><li>Bilobate with rounded lobes and long shaft (&gt;10 µm).</li></ul></td><td>Piperno and Pearsall 1998; Piperno 2006; Neumann et al., 2009.</td></tr><tr><td>Panicoideae</td><td><ul><li>Bilobates panicoid type.</li><li>Bilobates concave outer margin long/short shaft.</li><li>Bilobates convex outer margin outer margin short shaft.</li><li>Quadra-lobates/ crosses.</li></ul></td><td><ul><li>Bilobate that is symmetrical, with rounded lobes. Shaft &lt;10 µm).</li><li>Bilobates with lobes curving inwards with either long shaft (&gt;10 µm) or short shaft (&lt;10 µm).</li><li>Bilobate with rounded lobes and short shaft (&lt;10 µm).</li><li>Equidimensional bodies with four lobes</li></ul></td><td>Fredlund and Tieszen 1994; Pieperno 2006; Fahmy 2008; Rossouw 2009; Neumann et al. 2009; Mercader et al. 2010; Novello et al., 2012.</td></tr><tr><td>Chloridoideae</td><td><ul><li>Saddle (Figure 4n).</li><li>Saddle squat.</li></ul></td><td><ul><li>Saddle bodies with two opposite convex edges and two opposite concave edges in top view.</li><li>Saddle with side notches and a much longer axis than its tangential line.</li></ul></td><td>Piperno 2006; Rossouw 2009; Neumann et al. 2009; Novello et al. 2012; Mercader et al., 2010.</td></tr><tr><td>Undifferentiated grasses</td><td><ul><li>Bulliforms (Figure 4k).</li></ul></td><td><ul><li>Parallelepipedal bulliform cells.</li></ul></td><td>Madella et al. 2005; Neumann et al. 2009; Novello et al., 2012.</td></tr><tr><td>Palm trees</td><td><ul><li>Globular echinate (palm type) (Figure 4c).</li></ul></td><td><ul><li>Globular echinate, with defined spines.</li></ul></td><td>Albert et al. 2006; 2009; Piperno 2006; Barboni et al., 2007; 2009.</td></tr><tr><td>Woody taxa (Dicot)</td><td><ul><li>Globular granulate (Figure 4a).</li><li>Globular verrucate (Figure 4d).</li><li>Tracheids (Figure 4g).</li><li>Sclereids (Figure 4e).</li></ul></td><td><ul><li>Spheroid/ spherical with fine knobs or knots, grainy.</li><li>Spheroid/spherical with irregularly shaped wart-like processes.</li><li>Tracheids.</li><li>Silicified elongate to slightly curved treachery tissue.</li></ul></td><td>Strömberg 2004; Madella et al. 2005; Albert et al. 2005; Piperno 2006; Neumann et al. 2009.</td></tr><tr><td>Herbaceous taxa</td><td><ul><li>Globular psilate, elongate spiny.</li></ul></td><td><ul><li>Spheroid/spherical with smooth to sub-smooth surface.</li></ul></td><td>Madella et al. 2005; Piperno 2006; Neumann et al., 2009.</td></tr><tr><td>Cyperaceae</td><td><ul><li>Achene types, hat shapes (Figure 4h).</li></ul></td><td><ul><li>Pentagonal or hexagonal shape, with psilate surface and a central rounded cone.</li></ul></td><td>Ollendorf 1992; Piperno 2006; Neumann et al., 2009.</td></tr></tbody></table>
### 7.3.2 Data analyses

Morphotypes with >2% occurrence were plotted against sampling depths and age estimates using TILIA software (Grimm 2007). The zonation is determined statistically by constrained incremental sum-of-squares analysis (CONISS), a component of the TILIA and TILIA GRAPH software (Grimm 2007), based on sequential samples that coincide with the geological age bracket from which they were sampled.

We calculated three phytolith indices: (i) tree cover density (D/P) to distinguish grassland versus wooded vegetation, whereby a high D/P ratio indicates woody vegetation, and a low D/P ratio indicates open grassland, (ii) climate index ((I<sub>C</sub>) to estimate the temperature gradient, whereby high I<sub>C</sub> indicates cool climates, and low I<sub>C</sub> indicates warmer climates, and (iii) aridity index (I<sub>ph</sub>) to estimate aridity-humidity gradient across time (Alexandre *et al.* 1997; Diester-Haas *et al.* 1973), whereby a high I<sub>ph</sub> indicates arid while low I<sub>ph</sub> indicates moist-conditions (Alexandre and Bremond 2009; Bremond *et al.* 2005a, Bremond *et al.* 2005b; 2008; Neumann *et al.*, 2009).

The D/P index is calculated as the ratio of diagnostic woody dicotyledons morphotypes (globular granulate/ornate) versus diagnostic grass short cell phytoliths (GSCPs) (saddles+bilobates+crosses+polylobates+trapeziform rondels) (Alexandre *et al.* 1997; Bremond *et al.* 2005b; Bremond *et al.* 2008; Neumann *et al.* 2009). The I<sub>ph</sub> index is calculated as the ratio of Chloridoideae (saddle) versus the sum of Chloridoideae (saddle) and Panicoideae (cross + bilobates + polylobates) (Bremond *et al.* 2005b; Neumann *et al.* 2009). The I<sub>C</sub> index is the ratio of Pooideae C<sub>3</sub> grasses (trapeziform and keeled rondels) versus C<sub>4</sub> Panicoideae and Chloridoideae grasses (saddles + bilobates + crosses + polylobates+trapeziform) (Bremond *et al.* 2008).

## 7.4 RESULTS

### 7.4.1 Temporal changes

Temporal variation in phytolith assemblages are presented in summary diagrams which shows changes in the proportion of the various morphotypes (Figure 5). Five main taxonomic categories are identified and classified into: (i) C<sub>3</sub> grasses (Pooideae), (ii) C<sub>4</sub> grasses (Panicoideae, Chloridoideae and Aristidoideae), (iii) other grasses (undifferentiated grasses), (iv) tree-shrub-herbs (woody and other taxa), and (v) aquatic taxa (palms and sedges).

A total of 18,679 phytoliths were assigned to 41 different morphotypes. Concentrations of phytoliths averaged 747 per sample, of which around 61% were grasses, 12% trees and shrubs, while palms and sedges morphotypes accounted for 2% each. Non-diagnostic morphotypes accounted for 0.01% only. Of the 11,400 grass phytoliths 91% are diagnostic. Grass phytoliths were the most prominent component in all samples except for three from the Olorgesailie Fm. (R9, R16 and R17) which were dominated by trees/shrubs morphotypes. Variations in the phytolith assemblage where clustered into zones using CONNISS; these vegetation based divisions were found to correspond closely with the chronostratigraphic units (Figure 5).

#### 7.4.1.1 Upper Olorgesailie formation zone (c. 670 ka to 500 ka)

The phytolith assemblages in the Upper Olorgesailie Fm. zone show greater abundance of trees/shrubs morphotypes relative to the grass morphotypes (Figure 5). C₄ Aristidoideae morphotypes are consistently low in this unit. Palm and sedge phytoliths are present in moderate abundance in nearly all of the six samples from this zone. Phytolith indices, I<sub>C</sub>, I<sub>ph</sub> and D/P in the Olorgesailie Fm zone are as follows:- mean and max. respectively I<sub>C</sub> (0.3, 0.6), I<sub>ph</sub> (0.5, 0.7) and D/P (0.4, 1.0). The I<sub>C</sub> maximum is recorded in the sample prior to 650 ka while I<sub>ph</sub> and D/P maxima are recorded around 650 ka (Figure 6).
<figure><img src="image_40.png" /><figcaption>**Figure 5.** Phytolith relative abundance plotted against sample levels 10 – 250, representing the combined stratigraphic sequence through the Oltulelei and upper Olorgesailie formations. Note that actual sample intervals are variable in thickness but are equalized for this diagram.. See text for explanation of phytolith zones. CONISS = constrained incremental sum-of-squares analysis, a component of the TILIA and TILIA GRAPH software (Grimm 2007).</figcaption></figure>
<figure><img src="image_41.png" /><figcaption>**Figure 6.** Phytolith indices plotted against samples. Climate index (Ic) increases with cool conditions, Aridity index (Iph) increases with low precipitation and Tree cover density (D/P) increases with more wooded vegetation structure. Graph plotted with older to younger going from right to left. Geological markers indicate with dotted red lines.</figcaption></figure>

### 7.4.1.2 Olkesiteti mb zone (c. 320 ka to 220 ka)

This zone is separated from the underlying Olorgesailie Fm. zone by the c. 180,000 year unconformity (Behrensmeyer *et al.* 2002; 2018). Phytolith assemblages are mostly dominated by grasses, especially C₄ Panicoideae. The Olkesiteti mb zone represents phytolith data for samples R10 to R24 and marks the beginning of reduced frequencies of trees/shrubs phytoliths with increased GSCPs dominated by C₄ Panicoideae morphotypes (Figure 5). Through the zone there is a significant increase in palm phytoliths, which had virtually disappeared following the unconformity. Interestingly, this variation, along with increased GSCPs and reduction of trees/shrubs morphotypes, appears to correspond with the geological marker in the unit. Phytolith preservation is good, as indicated by the low count in the indeterminate category. Phytolith indices, Ic, Iph and D/P in the zone are as follows:- mean and max. respectively Ic (0.2, 0.3), Iph (0.3, 0.5) and D/P (0.1, 0.1) (Figure 6).

### 7.4.1.3 Oltepesi mb zone (c. 220 ka to 64 ka)

The Oltepesi mb zone is marked by increased GSCPs, especially C₄ Panicoideae morphotypes, similar to the Olkesiteti mb zone. However, in this zone a slight increase in trees/shrubs morphotypes is evident, exceeding 15% in most of the samples. The zone is further sub-divided into two sub-zones, viz. Oltepesi mb zone-a and -b following the CONNISS clustering.

a) Sub-zone Oltepesi mb-a exhibits a continuation of C₄ Panicoideae and C₄ Chloridoideae grass dominance. Palm phytoliths are rare but an increase in tree/shrub phytoliths >15% occurs, especially in samples R26 (100) and R27 (90) (Figure 5).

b) Sub-zone Oltepesi mb-b is characterized by trees/shrubs and C₄ Panicoideae grasses with the exception of sample R33 (30), which has a high occurrence of C₃ Pooideae grasses, while both C₄ Panicoideae and Chloridoideae grasses are relatively low in this sub-zone. Phytolith indices, Ic, Iph and D/P in the entire zone are as follows:- mean and max. respectively Ic (0.1, 0.4), Iph (0.3, 0.4) and D/P (0.1, 0.2) (Figure 6).
### 7.4.2 Spatial variation

We documented variations in phytolith assemblages across the three localities sampled from three geological sections, OLT05-02, B05-04 and G08-01 (Figure 2). The distance between Localities OLT and B is *c.* 2.2 km and between B and G *c.* 2.5 km, in the east-west direction (Behrensmeyer *et al.* 2018). Summary phytolith diagrams (Figure 7) show percentage occurrence of selected morphotypes identified and classified by taxonomic affiliation, which are then grouped into five major categories: (i) C₃ grasses, (ii) C₄ grasses, (iii) woody and herbaceous taxa, (iv) Other taxa, and (v) riparian/aquatic taxa. The percentages are plotted for each sample for the period between *c.* 320 ka and *c.* 220 ka (Figure 7).

OLT05-02 samples, which is farthest east, show two major clusters (Figure 7). The lower three samples are characterized by low occurrence of C₄ Chloridoideae grasses (<10%) and relatively higher occurrence of trees/shrubs and dicots phytoliths at >20%. The upper cluster is dominated by grass morphotypes, derived especially from C₄ Panicoideae and Chloridoideae. Chloridoideae morphotypes increase to more than 10% in this cluster. C₃ Pooideae morphotypes are more or less consistent across all six samples. Palm and sedge phytoliths are rare in all samples. Phytolith indices, mean and max. respectively for the OLT05-02 samples are as follows: Ic (0.7, max. 1.6), Iph (0.3, 0.4) and D/P (0.1, 2.1) (Figure 8).

B05-04 samples are similar except for sample number R19 (*c.* 320 ka), which is dominated by tree/shrub morphotypes with a high occurrence of 60% dropping sharply to 20% or less in the subsequent samples towards *c.* 220 ka. Also present in low frequencies in this sample (R-19) are palm phytoliths, which are absent in the other samples in this section. Sedges are present in low percentages only across all five samples. Phytolith indices, mean and max. respectively for the B05-04 samples are as follows: Ic (0.5, max. 0.6), Iph (0.5, 0.6) and D/P (0.5, 0.6) (Figure 8).

G08-01 samples from the site situated farthest to the west, are divided into two major clusters that correspond with the red soil zone, which is geologically significant as the oldest unit of the Oltulelei Fm. in this locality (Behrensmeyer, *et al.* 2018) (Figure 7); the top of the red soil forms the 'geological marker' indicated in Figure 5. The lower cluster consists of samples R35, R36 and R37. Sample R37 differs from the rest in that it has the highest occurrence grass morphotypes coupled with lowest occurrence of tree/shrub morphotypes (10%). The upper cluster (R39, R41, and R42) is characterized by the presence of phytolith morphotypes from all categories. Palm phytoliths are present in significant frequencies except for R38 (*c.* 320 ka), which is notable for its high proportion of dicots, trees and shrubs.

We calculated phytolith indices for only five samples because it was not possible to do so for sample R38; C₄ grass morphotypes in this sample were absent, and extremely low C₃ Pooideae and tree/shrub morphotypes did not permit calculation of indices. Phytolith indices, mean and max. respectively for the B05-04 samples are as follows: Ic (0.6, max. 0.8), Iph (0.3, 0.5) and D/P (2.3, 7.5) (Figure 8).

## 7.5 DISCUSSION

### 7.5.1 Temporal vegetation change in the Olorgesailie basin (*c.* 670 ka to 64 ka)

Temporal changes in the vegetation cover and structure correspond to a relatively stable tectonic intervals in the basin around 670 ka to 500 ka, when vegetation structure was characterized by wooded grasslands as indicated by a higher D/P index (>0.5). The landscapes during this time window were characterized by riparian habitats and fresh water resources indicated by palms and sedges (Albert *et al.* 2009; Ashley *et al.* 2010 a, b; Bamford *et al.* 2006). Iph index suggests moderately moist conditions in the upper Olorgesailie Formation. After the *c.* 180,000 years unconformity, vegetation cover transitioned to C₄ Panicoideae dominated grasslands, that
<figure><img src="image_42.png" /></figure>

**Figure 7.** Phytolith relative abundance plotted against samples from the same 100 ka time interval for Localities OLT, B and G, which shows kilometre-scale landscape variability in local vegetation across the Olorgesailie basin. In G08-01, 'Top of red soil' = 'Geological Marker' in Figures 5 and 6. See text and caption to Figure 5 for further information.
<figure><img src="image_43.png" /><figcaption>**Figure 8.** Olorgesailie phytolith indices plotted against samples for localities OLT, B and G. Graphs plotted with older to younger going from right to left. Climate index (Ic) increases with cool conditions, Aridity index (Iph) increases with low precipitation and Tree cover density (D/P) increases with more wooded vegetation structure. Geographically, OLT05-02 is farthest east, B05-04 in the middle, and G08-01 is farthest west (Figure 2).</figcaption></figure>

fluctuates subtly through to c. 64 ka. Ic and Iph indices suggest warm and moist conditions. Vegetation cover between c. 220 ka and 64 ka, was stable and dominated by C4 Panicoideae grasslands with low proportions of woody elements. Wetlands were present through to c. 220 ka. As mentioned earlier, variation corresponds to lithostratigraphic units.
### 7.5.2 Vegetation heterogeneity across the Olorgesailie basin (c. 320 ka to 220 ka)

Vegetation heterogeneity existed across the landscapes of the Olorgesailie basin between c. 320 ka and c. 220 ka. Within locality OLT, toward the eastern part of the rift basin (Figure 2), vegetation cover was initially dominated by woody elements that shifted towards C₄ Panicoideae grasslands. Palms and sedges were rarely present. Locality B, near the northern shoulder of Mt. Olorgesailie, was also dominated by C₄ Panicoideae grasslands except around c. 320 ka, which was marked by high dominance in woody vegetation. Sedges were rarely present and palms completely absent. Locality G on the western side of Mt. Olorgesailie was consistently dominated by woody and dicot vegetation, with abundant palms. C₃ Pooideae grasses across the three localities follows an east-west declining trend and are more prominent across the eastern and central localities (B and OLT) than at Locality G. This suggests that topographic complexity in the basin also influenced vegetation variation across the palaeolandscapes at least 5 km distance. Mt. Olorgesailie, which is today characterized by C₃ vegetation, likely also was a source of the C₃ Pooideae phytoliths input into the basin during the Oltulelei Fm. The evidence overall indicates considerable spatial variation in vegetation structure across the basin during the period of sedimentation.

### 7.5.3 Palaeoanthropological significance of vegetation data

The phytolith data presented here represent temporal resolution of 10⁴⁻⁵ years over a total interval of c. 600,000 years and are currently the only comprehensive outcrop-based data in East Africa for inferring vegetation during the Middle to Late Pleistocene transition in early hominin technology from Acheulean to Middle Stone Age (MSA) tools, by c. 350 ka to 320 ka (Brooks et al. 2018; Potts et al. 2018). Before the c. 180,000-year erosional phase, the vegetation structure associated with the late Acheulean technology at Olorgesailie was more wooded, and included wetlands/riparian resources, contrasting with the vegetation structure associated with MSA technology, which was dominated by warm and moist-adapted C₄ Panicoideae grasslands. This corresponds with a marked change in the geology and lithology of the basin between c. 500 and 320 ka, which exhibited a shift to a landscape with fluvial channels, flood plains and spring deposits (Behrensmeyer et al. 2018; Potts et al. 2018). The vegetation change was accompanied by large mammal turnover, evidenced by the paleontological evidence in the southern Kenyan rift (Potts et al. 2018). Herbivores may have played a significant role in engineering the vegetation structure as it shifted from more wooded to open grasslands in the basin (Potts et al. 2020). These dynamics could have influenced human adaptive strategies that led to new technological innovations (Brooks et al. 2018; Potts et al. 2020).

Vegetation heterogeneity, specifically the occurrence of a mosaic of riparian, grasslands and woodland patches in the time interval between 320 ka and 220 ka, suggests a variety of habitats that availed key resources for hominins and offered attractive spots for food resources. Such mixed habitats have been inferred at other prehistoric sites such as Olduvai and Awash and proved to be of palaeoanthropological significance (Albert et al. 2009; Ashley et al. 2010; Bamford et al. 2006; Barboni et al. 1999).

## 7.6 CONCLUSIONS

Phytolith data show that vegetation structure and cover in the Olorgesailie basin was more wooded prior (c. 670 ka to 500 ka) to the c. 180,000 year unconformity. Riparian habitats were present with subtle variation between palaeolandscapes. Trees and shrubs fluctuated between landscapes while grasslands remained stable. From 320 ka to 64 ka vegetation cover shifted to grasslands dominated by C₄ Panicoideae with some riparian habitats. Between c. 320 ka and 220 ka, our evidence shows that relatively adjacent habitats in the basin included a diversity of open grasslands, woodland, and riparian elements.
Phytolith data from this study assist in developing an understanding of local palaeoen-
vironments with which early hominins interacted during the Pleistocene (c. 670 ka to 64 ka).
The data suggest that late Acheulean technology in the southern Kenya rift was associated with
more woody vegetation structure than early MSA technology, which appears to have coincided
with grassy landscapes in the Olorgesailie basin. This technological transition at Olorgesailie
represents the oldest example currently known of the replacement of the Acheulean by the MSA
(Brooks et al. 2018; Deino et al. 2018). We propose that this important transition may have
occurred in response to changing vegetation and food resources available to the fauna, and may
help to explain the replacement of large-bodied by smaller-bodied herbivores that were increas-
ingly reliant on mixed vegetation diets (Potts et al. 2020). The varied habitats present in the basin
offered critical resources such as fresh water and forage that would have sustained hominins and
other animals.

In conclusion, vegetation dynamics in Olorgesailie during the Pleistocene reflected responses to both precipitation variability and tectonic processes. The vegetation data presented here are significant in that they are directly extracted from and related to fossil- and artifact-bearing outcrops and shed new light on the evidence for interactions between hominins and other faunal and floral communities in the basin. We postulate that such interactions likely played a critical role in shaping hominin behavior and technological innovations.

ACKNOWLEDGEMENTS

Our sincere gratitude goes to the following institutions, National Museums of Kenya (NMK), University of Cape Town, Smithsonian Institution, and University of Calgary. Support from the Peter Buck Fund for Human Origins Research (Smithsonian) is much appreciated. Acknowledged. We also thank Alan Deino for his long-term collaboration on the geological dates discussed in this paper; Jennifer Clark for her assistance in all the logistics that involved the Smithsonian Institution and for assisting with the figures; Drs. Veronica Muiruri and Stephen Rucina for the technical provisions during analyses at the Palynology and Paleobotany lab, NMK.

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<figure><img src="image_44.png" /></figure>

Taylor & Francis

Taylor & Francis Group

http://taylorandfrancis.com
CHAPTER 8

Sedimentological, palynological and charcoal
analyses of the hydric palustrine sediments from
the Lielerai-Kimana wetlands, Kajiado, southern
Kenya

Esther N. Githumbi<fnref n="1" />

*Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden*

Colin J. Courtney Mustaphi<fnref n="2" />

*Department of Environmental Sciences, Geoecology, University of Basel, Basel, Switzerland*

Robert Marchant

*Department of Environment and Geography, Institute for Tropical Ecosystems, University of York, York, United Kingdom*

ABSTRACT: Intermittent and sometimes ephemeral wetlands found in savannah ecosystems are subject to complex hydrological and geomorphological processes that influence vegetation and fire patterns, and their use by humans, cattle and wildlife. Today these wetlands are impacted by changes in land use, climate, and wildlife use. Small wetlands in semi-arid climates are dynamic ecosystems that respond rapidly to biological, physical and chemical processes and accumulate sedimentary deposits making them excellent archives of past environmental changes. The Lielerai-Kimana wetlands in the Greater Amboseli Ecosystem of southern Kenya are located within the current protected area network. A 384 cm long palustrine sediment core was recovered from the Lielerai-Kimana wetlands, radiometrically dated, and used for sedimentological, palynological and charcoal analyses. The ²¹⁰Pb (n = 16 ages) and ¹⁴C (n = 10 ages) results suggest a complex depositional pattern covering c. 1500 years. The mismatches between ²¹⁰Pb and ¹⁴C date estimates suggest some degree of sediment mixing which may prevent centennial-scale interpretation of the palaeoenvironmental record. The sediments are characterised by a high silt content from

<footnote n="1">¹Other affiliation: *Department of Biology and Environmental Science, Linnaeus University, Kalmar, Sweden*</footnote>

<footnote n="2">²Other affiliation: *Water Infrastructure and Sustainable Energy (WISE) Futures, Nelson Mandela African Institution of Science & Technology, Tengeru, Arusha, Tanzania; and York Institute for Tropical Ecosystems, Department of Environment and Geography, University of York, York, United Kingdom*</footnote>
1500–600 cal yr BP with the organic content increasing from 600 cal yr BP to the present. The pollen data show little changes in vegetation composition, suggesting a mosaic of savannah, woody savannah, riparian, and montane forest persisted throughout the period of deposition. Charcoal and organic content suggest the continuous presence of herbaceous fuels at the coring site from 600 cal yr BP to the present. The results highlight the spatiotemporal heterogeneity and complexity of wetland records across the semi-arid landscapes of Amboseli during the Late Holocene. Further studies on hydroclimate and vegetation change, disturbance ecology (fire, erosion, bioturbation), and human-environment interactions would further develop our understanding of the environmental history and drivers of environmental change across these ecosystems that are increasingly under human land use pressures.

## 8.1 INTRODUCTION

Amboseli is an important ecosystem in southern Kenya due to its high biodiversity, long history of pastoralism, rapidly developing agricultural potential, and subsequent land-use changes over the past decades. High levels of tourism since the 1960s (Western 1973, 2007; Western et al. 2020) make Amboseli an important contributor to Kenya's gross domestic product (GDP) and the livelihoods of local communities (Hodgson 2000; Makindi 2016). Amboseli has experienced, and continues to experience, wide-scale yet spatially complex habitat changes such as: *Vachellia xanthophloea* woodland reduction, riparian and wetland fluctuation, introduced agriculture and a proliferation of ruderal plant species (Western and Van Praet 1973). Within semi-arid regions, such as the Amboseli, water is a crucial natural resource and ecosystem service. Changes in livelihood strategies from pastoral to sedentary has led to increased pressure on water resources for farming and irrigation (Okello and Kioko 2011; Wishitemi et al. 2015). Amboseli wetlands are intermittently distributed across the semi-arid savannah landscape and have complex responses to hydroclimate, land-use and land cover changes, defaunation and wildlife management (Meijerink and Wijngaarden 1997). Increased densities of wildlife populations outside protected areas due to fencing along migration corridors (Kenya Wildlife Service 2009; Osipova et al. 2018) and fencing in some of Amboseli's wetlands (Okello and Kioko 2011) has been reported. The Amboseli Ecosystem Management Plan 2008–2018 (Kenya Wildlife Service 2009) and Kenya Wetlands Atlas (MEMR 2012) identified wetlands as an exceptional resource value for the Amboseli ecosystem that are susceptible to rapid and irreversible change with complex social co-benefits and potential negative impacts on biodiversity and conservation. Palaeoenvironmental records developed from wetland ecosystem sedimentary archives can provide a long-term context for modern ecosystem changes and develop data suitable for characterising the wetlands, and their histories, as part of developing evidenced-based support for management (Gillson and Marchant 2014; Githumbi et al. 2020).

The abundance of wetlands in Amboseli enabled five palaeoecological studies, focused on a variety of proxies, to provide information relevant to understanding different aspects of environmental, ecological and human-environment interaction change during the Late Holocene (last c. 4200 years). Understanding how the various wetlands responded to large-scale controls (climate variability) and internal controls (hydrological connectivity, topography) is necessary when utilising wetland palaeoenvironmental records to observe temporal change and compare changes across a landscape. Palynological analyses published from Amboseli wetlands, include Namelok (Rucina et al. 2010) and Esambu, Kimana and Ormakau (Githumbi 2017) and were presented in summary formats for discussion alongside archaeological insights (Githumbi et al. 2018a, Shoemaker 2018) and carbon accumulation in wetlands (Gallego-Sala et al. 2018). The oldest radiocarbon dated published record from the Amboseli wetlands is currently from Indoinyo-Esambu, which dates back to c. 5000 cal yr BP, while the Namelok record covers the past c. 3000 cal yr BP. The radiocarbon dated sediment core presented here from the Lielerai-Kimana
dates back to c. 1500 cal yr BP. Sedimentological, geochronological, palynological and charcoal
data from the Lielerai-Kimana sediment core are used to characterise the sediments, explore
the limitations and opportunities of the geochronological results, and interpret the pollen and
charcoal results. The findings are discussed in relation to the history of wetland dynamics in the
Amboseli area of southern Kenya.

8.1.1 Study site

Amboseli is located in southern Kenya between the northern base of Kilimanjaro, near the Kenya-Tanzania border, Tsavo West National Park and the Chyulu Hills (Figure 1). A semi-arid savannah and scrubland ecosystems, the Amboseli basin occupies c. 3000 km² and experiences bimodal rainfall distribution. Rainfall patterns are determined by the African monsoon, which is, in turn, driven by the latitudinal migration of the Intertropical Convergence Zone (ITCZ) and its interaction with more local climate systems and topographic feedbacks (Hulme 1996; Marchant et al. 2007). Precipitation mainly falls in two rainy seasons: March-May and October-December. Average annual precipitation is 586 mm year⁻¹ although with considerable interannual variation (range 226 to 990 mm year⁻¹) from 1979 to 2009 (Githumbi 2017). An overall increase in temperature (daily minimum and maximum) was observed between 1976 and 2001, however, there was little change in precipitation (Altmann et al. 2002). Today, Amboseli supports a wide range of wildlife including ungulates, carnivores, and birds, that co-exist with pastoralist and agricultural land uses, making it an important wildlife conservation area and designated important bird area (IBA). Several of the wetlands across Amboseli are crucial for wildlife migrations among the network of protected (Kenya Wildlife Service 2009; Osipova et al. 2018), however, with

<figure><img src="image_45.png" /></figure>

**Figure 1.** Map of the Lielerai-Kimana wetlands and study site (red boxes). (A) Inset map of Africa and (B) East Africa. (C) The Kimana Sanctuary Lielerai-Kimana wetlands and riparian forests along the Kimana River, which flows north and then east. The Cyperaceae and Poaceae covered riparian wetland is outlined with black and the coring location is shown with a black circle (coordinates: 2.748833 S, 37.515367 E, 1222 m asl). The ‘V’ symbol indicates the location and perspective of the inset photograph D, and Kenyan road C102. (D) Oblique air photograph of the wetland showing the coring location (black circle) and landscape features around the Kimana Sanctuary protected area (Courtney Mustaphi *et al.* 2014; Githumbi *et al.* 2014). Google Earth image dated 27 April 2014 (copyright CNES/Airbus and Google Inc.) Basemap imagery: Google Earth, 2020, http://earth.google.com/web/.
<figure><img src="image_46.png" /><figcaption>**Figure 2.** Photographs of landscapes and features around the Kimana wetland. (A) The coring location between the tall Cyperaceae and Poaceae dominated wetland. (B) Short Poaceae and Cyperaceae that cover parts of the southern end of the Kimana wetland. (C) The Hippo pool (viewed from the west facing southeast). (D) A biogeomorphological riverbank feature heavily influenced by *Hippopotamus amphibius* and *Crocodylus niloticus* entering and exiting the Kimana River (flowing to the left of photograph, northward). (E) The eastern margin of the Kimana Sanctuary viewing northeast showing the mosaic of barren ground, savannah, woody savannahs, and wetlands. (F) An example of crops grown in the Amboseli-Oloitoktok area. Photographs: A, Esther Githumbi, April 2014; B, D, E, Colin Mustaphi, March 2015; and C, F, Rob Marchant, March 2015.</figcaption></figure>

increasing anthropogenic land-use pressures and human-wildlife conflicts are increasing (Okello 2005).

The Amboseli landscape comprises of savannah and scrubland plains, lacustrine plains, wetlands, and volcanic footslopes (Meijerink and Wijngaarden 1997). The woody-grassy savannah landscapes are dominated by *Pennisetum* spp., *Cenchrus* spp., and African Acacia species (*Vachellia* and *Senegalia*, and referred in this paper as Acacias) (Figure 2). The Amboseli wetlands are located on the Kilimanjaro aquifer and they receive groundwater and surface runoff
primarily from the slopes of Mount Kilimanjaro (Grossmann 2008; Meijerink and Wijngaarden 1997). Amboseli wetlands are either spring fed (Enkongu, Esambu, Ormakau, Namelok) or riverine (Lielerai-Kimana) and highly modified through climatological, biological, geomorphological and hydrological processes. The wetlands overlie deep, well-drained and neutral pH soils developed from lava flows and partly reworked pyroclastic deposits of Pleistocene age (Williams 1972). These wetland areas are dominated by *Cyperus* spp. and *Sporobolus* spp., while *Vachellia* (Acacias), *Balanites*, *Commiphora*, *Euphorbia* and *Syzygium* dominate the adjacent woody savannas and scrublands.

The Lielerai-Kimana toponym comes from the Maa language, where ‘Lielerai’ refers to the yellow fever trees (*Vachellia xanthophloea*) and ‘Kimana’ means ‘a continuous circle’. The Lielerai-Kimana wetland is fed by the Kimana River, which flows through the wetlands towards the Chyulu Hills. Parts of the wetland complex was under various forms of protected area status that have included ecotourism and community-based conservation (Githumbi et al. 2018a; Meguro and Inoue 2011) and is an ecological hotspot for wildlife migration and is a hippopotami breeding site.

## 8.2 MATERIALS AND METHODS

### 8.2.1 Field methods

The Lielerai-Kimana core site was located, within the Kimana Sanctuary (also known as *Sidai Oleng*), at 2.748833°S, 37.5151367°E (1222 m asl). Today the area around Lielerai-Kimana is a Cyperaceae-covered wetland with hydric soils and palustrine sediments (Figures 2A, 2B). In July 2014, the profile of the sediments beneath the wetlands were determined through probing using fiberglass rods. A coring location was then chosen where the organic sediment accumulation seemed to be high and sandy layers appeared to be absent. Then the sediments were cored using a hand operated, 50 cm long, 5 cm diameter hemicylindrical Russian peat corer (Jowsey 1966). Sediment cores from two overlapping parallel boreholes were obtained. Together the parallel cores contained the complete sedimentary sequence and reached a maximum depth of 384 cm (Courtney Mustaphi et al. 2014; Githumbi 2017). Upon recovery, the core sections were wrapped in plastic and aluminium foil, and transferred into split plastic PVC pipes for transport. The sediment cores were then transported to the Palynology and Palaeobotany Section of the National Museums of Kenya (NMK; Nairobi, Kenya) where they were placed in cold storage at 4°C. Subsamples were later extracted at NMK, and analyses were undertaken at NMK and the University of York (UK).

### 8.2.2 Laboratory methods

#### 8.2.2.1 Geochronology

Ten accelerator mass spectrometer (AMS) radiocarbon dates were obtained from the Lielerai-Kimana sediment core (Table 1). Two bulk sediment subsamples were sent to Direct AMS (Bothell, WA, USA) that were acid-base-acid washed, combusted, graphitised and measured using a National Electrostatics Corporation (NEC) 1.5 SDH Compact Pelletron 500 kV AMS. Two bulk sediment subsamples were sent to the ¹⁴CHRONO laboratory (Queen's University Belfast, Northern Ireland) and acid wash pre-treated prior to combustion to CO₂, graphitization and AMS using a NEC 0.5 MV compact accelerator. Six sediment subsamples were wet sieved using a 63 µm mesh and the fine organic detrital fraction (<63 µm) was graphitised and dated at the East Kilbride facility of the SUERC Radiocarbon Laboratory (University of Glasgow) using either the National Electrostatic Corporation 5 MV tandem AMS or 250 kV single-stage AMS. Radiocarbon ages (¹⁴C years BP) were calibrated using the IntCal13 curve (Reimer et al. 2013). Calibrated ages are presented in years BP (Before Present, CE 1950) by convention.
<table><caption>**Table 1.** Alpha counter radioactivities (counts per second or Bq) and CRS model calendar age results of $^{210}$Pb dating the uppermost sediments of the Lielerai-Kimana sediment core collected in CE2014 (–64 yr BP). Note that samples below $^{210}$Pb background radioactivities (34–40 cm) do not produce CRS calendar age estimates. Acronyms: BP, before present AD1950; CRS, constant rate of supply model; NA, not applicable, ages not modelled.</caption><thead><tr><th>Depth (cm)</th><th>Dry weight (g)</th><th>Bulk density (g cm<sup>-3</sup>)</th><th>Corrected d <sup>209</sup>Po (counts)</th><th>Corrected d <sup>210</sup>Po (counts)</th><th><sup>210</sup>Pb activity <sup>209</sup>Po (Bq kg<sup>-1</sup>)</th><th><sup>210</sup>Pb-activity error &plusmn;1&sigma; (Bq kg<sup>-1</sup>)</th><th>CRS year BP</th><th>CRS 2&sigma; error (years)</th></tr></thead><tbody><tr><td>4–5</td><td>0.2523</td><td>0.2678</td><td>2073.30</td><td>134.25</td><td>0.06</td><td>23.55</td><td>2.16</td><td>-63</td><td>2.01</td></tr><tr><td>5–6</td><td>0.3035</td><td>0.3109</td><td>1654.24</td><td>95.75</td><td>0.06</td><td>17.50</td><td>1.89</td><td>-62</td><td>2.29</td></tr><tr><td>6–8</td><td>0.502</td><td>0.2614</td><td>973.14</td><td>69.73</td><td>0.07</td><td>13.10</td><td>1.66</td><td>-61</td><td>2.30</td></tr><tr><td>8–10</td><td>0.3801</td><td>0.2077</td><td>1760.26</td><td>88.46</td><td>0.05</td><td>12.13</td><td>1.36</td><td>-60</td><td>2.31</td></tr><tr><td>10–12</td><td>0.4117</td><td>0.2247</td><td>1490.22</td><td>85.34</td><td>0.06</td><td>12.77</td><td>1.46</td><td>-59</td><td>2.32</td></tr><tr><td>12–14</td><td>0.5203</td><td>0.2864</td><td>1375.20</td><td>135.30</td><td>0.10</td><td>17.35</td><td>1.61</td><td>-57</td><td>2.32</td></tr><tr><td>14–16</td><td>0.4018</td><td>0.2202</td><td>1434.21</td><td>88.46</td><td>0.06</td><td>14.09</td><td>1.59</td><td>-55</td><td>2.34</td></tr><tr><td>16–18</td><td>0.3981</td><td>0.2184</td><td>1486.22</td><td>139.46</td><td>0.09</td><td>21.63</td><td>1.97</td><td>-50</td><td>2.37</td></tr><tr><td>18–20</td><td>0.3977</td><td>0.2347</td><td>1421.21</td><td>113.44</td><td>0.08</td><td>18.42</td><td>1.85</td><td>-45</td><td>2.40</td></tr><tr><td>20–22</td><td>0.4735</td><td>0.2839</td><td>1999.29</td><td>218.55</td><td>0.11</td><td>21.19</td><td>1.57</td><td>-38</td><td>2.45</td></tr><tr><td>22–24</td><td>0.3152</td><td>0.2079</td><td>1768.26</td><td>150.91</td><td>0.09</td><td>24.85</td><td>2.17</td><td>-24</td><td>2.58</td></tr><tr><td>24–26</td><td>0.3312</td><td>0.1887</td><td>1197.18</td><td>53.08</td><td>0.04</td><td>12.28</td><td>1.77</td><td>-15</td><td>2.65</td></tr><tr><td>26–28</td><td>0.2737</td><td>0.1577</td><td>1147.17</td><td>53.08</td><td>0.05</td><td>15.51</td><td>2.23</td><td>4</td><td>3.01</td></tr><tr><td>28–30</td><td>0.1683</td><td>0.1607</td><td>1163.17</td><td>18.73</td><td>0.02</td><td>8.78</td><td>2.09</td><td>20</td><td>3.36</td></tr><tr><td>30–32</td><td>0.2761</td><td>0.1824</td><td>1835.27</td><td>38.51</td><td>0.02</td><td>6.97</td><td>1.16</td><td>37</td><td>3.84</td></tr><tr><td>32–34</td><td>0.2236</td><td>0.1541</td><td>1430.21</td><td>23.94</td><td>0.02</td><td>6.87</td><td>1.45</td><td>79</td><td>7.24</td></tr><tr><td>34–36</td><td>0.2231</td><td>0.1345</td><td>1341.20</td><td>15.61</td><td>0.01</td><td>4.79</td><td>1.24</td><td>NA</td><td>NA</td></tr><tr><td>36–38</td><td>0.2042</td><td>0.1272</td><td>1170.17</td><td>9.37</td><td>0.01</td><td>3.60</td><td>1.2</td><td>NA</td><td>NA</td></tr><tr><td>38–40</td><td>0.2425</td><td>0.1589</td><td>1567.23</td><td>18.73</td><td>0.01</td><td>4.52</td><td>1.07</td><td>NA</td><td>NA</td></tr></tbody></table>

Lead ($^{210}$Pb) dating of the uppermost sediments was done by drying sediment subsamples from intervals between 4–40 cm depth and measured through alpha spectroscopy at the University of Exeter, UK. A constant rate of supply (CRS) model of calendar age estimates with age estimate errors that have a Gaussian distribution (Appleby 2005) was developed with the core top (0 cm) set as –64 years BP, the year of core collection. $^{210}$Pb background activities were reached at 34–36 cm depth.

An age-depth model combining both calibrated $^{14}$C and $^{210}$Pb ages was developed using Bacon (Blaauw and Christen 2011) in RStudio version 1.3.959.

### 8.2.2.2 Sedimentological characterisation

The Lielerai-Kimana sediment cores were longitudinally split and surfaces cleaned flat with a knife and the composite stratigraphy of overlapping core drives was established in the laboratory. The cores were scanned at BOSCORF National Oceanography Centre (NOC), Southampton, UK, using a molybdenum tube ITRAX™ Core Scanner for µXRF semi-quantification of 36 elements at 500 µm resolution (Croudace and Rothwell 2015). The X-ray beam irradiated the centerline of the core using a 3 kW Mo X-ray tube typically run at 55 kV and 50 mA for x-radiography and 30 kV and 50 mA for the XRF scan. A Geotek multi-sensor core logger (MSCL-XYZ) with a Bartington MS2E magnetic susceptibility point sensor and a Konica Minolta spectrophotometer (quantified greyscale reflectance) scanned the cores at 0.5 cm intervals from 0–384 cm stratigraphic depth.
Loss-on-ignition (LOI) analysis (Heiri *et al.* 2001) was used to estimate organic matter content, carbonate content and residuals mean clastic particle size every 5 cm down core. Wet sediment subsamples were weighed dried at 105°C for 24 hours, then burned at 550°C for 5 hours and weighed, and ashed at 950°C for 3 hours and weighed, to calculate the dry weight (and dry bulk density), organic matter and carbonate contents respectively. Particle size distribution analysis used the Malvern Mastersizer 2000 laser granulometer (MEH/MJG180914). The binned particle size distributions were aggregated into percentage clay (<1–4 µm), silt (4–63 µm), and sand (63–2000 µm) fractions (Blott and Pye 2012). Bulk sediment C:N ratios for the top 111–0 cm at contiguous 1-cm intervals were measured using a CHN analyser at the University of Exeter, UK.

### 8.2.2.3 Sieved (>125 µm) charcoal analysis

For sieved charcoal analysis, subsamples of 1 cm³ of wet sediment were removed at a continuous 1 cm resolution. Samples were soaked in a sodium metaphosphate solution (Tsakiridou *et al.* 2020) for >24 hours and then wet sieved through a 125-µm mesh and the larger fraction was transferred to a gridded Petri dish. Charcoal pieces were identified and total charcoal was tallied through visual inspection and manipulated with a metal probing needle under a Zeiss Stemi 2000-C optical stereo microscope at 10–40 × magnifications and converted to sieved charcoal concentrations (pieces cm⁻³).

### 8.2.2.4 Pollen preparation and analysis

Wet sediment subsamples of 1 cm³ were extracted from the core at 20–cm intervals and processed for pollen analysis using sequential sediment digestions (Fægri and Iversen 1989). One tablet of exotic *Lycopodium* spores was added prior to pollen processing to act as a counter for calculating pollen concentration or estimation of absolute influx (Lund University batch number 3862, exotic count per tablet: 9666 ± 212.3). Subsamples were chemically digested, centrifuged, decanted, and rinsed with deionised water (or glacial acetic acid) after each digestion step. The digestion step included 10% HCl (room temperature), 10% KOH (room temperature), 50% HF (70°C), dewatering with glacial acetic acid, and acetolysis (Erdtman 1960; Fægri and Iversen 1989). Digested sediment residues were transferred into vials using 96% ethanol, centrifuged and decanted. Glycerine was added to match the volume of residue and then left for the ethanol to evaporate in an oven at 60°C then a droplet was mounted on standard microscope slides with a coverslip (Bennett and Willis 2001).

Pollen counts were conducted across horizontal line scans of the coverslips using a Leica DM4000B microscope at a magnification of 400×. Identifications were confirmed using a reference collection derived from pollen and herbarium specimens from the National Museums of Kenya and published pollen atlases (Bonnefille and Riotlet 1980; Hamilton 1976, 1982; Hamilton and Perrott 1980; Schüler *et al.* 2014). Pollen diagrams were plotted using C2 v.1.7.6 (Juggins 2003). The stratigraphically constrained cluster analysis using incremental sum of squares (CONISS, Grimm 1987) was used to delimit statistically significant assemblage zones of the relative abundances of all pollen types using a broken stick test (Bennett 1996). Pollen were grouped using published pollen atlases (Schüler and Hemp 2016), previously published pollen grouping (Githumbi *et al.* 2018a; Rucina *et al.* 2010), field observation of taxa, and ecology and habitat descriptions (Dharani 2011).

## 8.3 RESULTS

### 8.3.1 Chronology and stratigraphy

In total sixteen ²¹⁰Pb (Table 1) and 10 AMS radiocarbon dates (Table 2) were used in the development of the Bacon age-depth model (Figure 3; Blaauw and Christen 2011). The ²¹⁰Pb samples
<table><caption>**Table 2.** Reported AMS radiocarbon dates with IntCal13 calibrated ages with maximum 2σ error range (year BP, before present; Reimer *et al.* 2013) from the Lielerai-Kimana sediment core.</caption><thead><tr><th>Depth (cm)</th><th>Lab code</th><th>Age (¹⁴C years)</th><th>Calibrated age (year BP)</th><th>Material</th></tr></thead><tbody><tr><td>20–21</td><td>SUERC-64044</td><td>578 ± 37</td><td>600 ± 73</td><td>&lt;63 µm sieved organic detritus</td></tr><tr><td>40–41</td><td>SUERC-64045</td><td>526 ± 37</td><td>539 ± 88</td><td>&lt;63 µm sieved organic detritus</td></tr><tr><td>50–51</td><td>SUERC-57339</td><td>424 ± 37</td><td>486 ± 158</td><td>&lt;63 µm sieved organic detritus</td></tr><tr><td>50–51</td><td>SUERC-58881</td><td>500 ± 37</td><td>527 ± 96</td><td>&lt;63 µm sieved organic detritus</td></tr><tr><td>75–76</td><td>SUERC-64046</td><td>647 ± 37</td><td>605 ± 64</td><td>&lt;63 µm sieved organic detritus</td></tr><tr><td>100–101</td><td>UBA-26122</td><td>540 ± 24</td><td>543 ± 81</td><td>bulk sediment</td></tr><tr><td>100–101</td><td>SUERC-64047</td><td>630 ± 35</td><td>602 ± 58</td><td>&lt;63 µm sieved organic detritus</td></tr><tr><td>260–261</td><td>D-AMS 009667</td><td>946 ± 25</td><td>850 ± 67</td><td>bulk sediment</td></tr><tr><td>310–311</td><td>D-AMS 009668</td><td>455 ± 24</td><td>509 ± 27</td><td>bulk sediment</td></tr><tr><td>370–371</td><td>UBA-26122</td><td>1458 ± 31</td><td>1340 ± 44</td><td>bulk sediment</td></tr></tbody></table>

were from the top 40 cm of the core and the AMS radiocarbon dates ranged from the whole core. There is a high degree of uncertainty in the age-depth model from 650–100 cal yr BP due to the range of dates in this uppermost section, suggesting some degree of movement of old carbon.

The Lielerai-Kimana core was predominantly organic rich (c. 20%), poorly sorted, sandy and coarse silt sediments (c. 61% silt, c. 23% sand and c. 11% clay) and three broad lithological units were observed (Figure 4). The base of the core (384 cm) to 380 cm contained very poorly sorted dark grey sandy and coarse silts (mean particle size 70–170 µm) with light coloured sandy laminations. The second unit from 380–103 cm was a massive, visually homogeneous, poorly sorted, very dark brown organic sediment (10–25%), with increased clay content and less sand content (mean particle size 23–250 µm). The uppermost unit, from 103 cm to the top, contained very poorly sorted, medium dark brown sandy silt (mean particle size 80–250 µm) with a very high organic content (40–90%). C/N values were relatively high and variable within the measured section (Figure 3), 111–0 cm depth, carbon ranged in value between 16% and 48% while nitrogen ranged between 0.6% and 1.2%, the three C/N peaks are observed at 32 cm, 44 cm and 86 cm. Magnetic susceptibility ranges from 0 to 617.41 κ with a mean of 191.45 κ.

### 8.3.2 Charcoal

Sieved charcoal particle (>125 µm) concentrations ranged 2–5700 pieces cm³ with a mean of 329 (median of 104 pieces cm³) and 1σ standard deviation of 656. Throughout the core, but particularly in the uppermost section the charcoal concentrations are highly variable. Charcoal concentrations were generally <200 pieces cm³ from 384–100 cm and averaged 1000 pieces cm³ from 100–20 cm. Charcoal concentrations were <1000 pieces cm³ from 20–0 cm (Figure 4). When the charcoal concentrations were converted to charcoal accumulation rates (influx, pieces cm² year⁻¹), the pattern is very similar to the concentration values, with the exception of a slight increase in the top 30 cm that is not evident in the concentration values. Several surface sediment samples of 0–1 cm depth from different parts of the swamp (n = 13) were analysed using the same charcoal sieving method and averaged 17 pieces cm³ with a range of 0–162 pieces cm⁻³. The conspicuous increase in charcoal around 100 cm is concomitant with increased organic content and sands, and changes to the elemental composition measured by ITRAX (Figure 4).
<figure><img src="image_47.png" /><figcaption>**Figure 3.** (A) Alpha radioactivities and CRS model calendar age estimates (years BP) of the uppermost sediments of the Kimana sediment core. (B) Age-depth model iteration using IntCal13 calibration curve and default BACON settings.</figcaption></figure>

### 8.3.3 Pollen

Forty-six pollen taxa were identified from the Lielerai-Kimana sediment core and pollen-slide charcoal was also counted. Although the apparent variability of pollen relative abundances is relatively low, the CONISS zonation identified two significant pollen zones and the dendrogram showed insignificant zone breaks (subzones; Figure 5). The pollen taxa have been ordered by dominant growth form in Figure 5. The pollen assemblages are similar throughout the past 1500
<figure><img src="image_48.png" /><figcaption>**Figure 4.** Sedimentological results of the Kimana wetland sediment core and age-depth model estimated downcore ages (at left). The visual lithological description and sediment characterisation measurements of volume magnetic susceptibility, dry sediment bulk density, and loss-on-ignition results, particle size distribution summary and charcoal concentrations. C:N measurements were collected for the top 111-0 cm. Elemental ratios were calculated from ITRAX XRD results (cps units). Pollen zones delineated by horizontal lines from CONISS analysis of the pollen relative abundances (see Figure 5).</figcaption></figure>

years, consistent with the current savannah, wooded savannah, and riparian vegetation surround-
ing the site. Throughout the record the trees and shrubs have a combined mean value of c. 50%,
c. 24% and c. 26%. The herbaceous taxa are c. 31%, the aquatics c. 12% and the grass c. 6%.
The dominating taxa occurring above >2% throughout the record are *Vachelia* (Acacia) c. 3%,
*Carissa* c. 2%, *Polyscias* c. 2%, *Balanites* c. 2%, *Podocarpus* c. 3%, *Euphorbia* c. 3%, *Com-
melina* c. 3.7%, *Commiphora* c. 2.6%, *Asteraceae* c. 2.8%, *Amaranthaceae* c. 2.6%, *Cyperaceae
* c. 7%, *Typha* c. 3.5% and *Poaceae* c. 5%. The lowermost significant pollen assemblage zone 1,
from the core bottom to c. 900 cal yr BP (385 to 230 cm) has tree pollen abundances of c. 24%,
shrub pollen c. 27%, herbs c. 31%, aquatics c. 12% and grasses c. 6%. The uppermost significant
pollen assemblage zone 2, from c. 900 cal yr BP to present (230 cm to the top) is divided into
two subzones: zone 2a (from c. 800–500 cal yr BP, 230–90 cm) with tree pollen abundances of
c. 24%, c. 27% shrub pollen, c. 31% herbs, c. 12% aquatics and grasses c. 6%. The topmost
subzone 2b (from c. 500 cal yr BP to present, 90–0 cm) shows tree pollen abundances of c. 26%,
c. 25% shrub pollen, c. 31% herbs, c. 12% aquatics, and c. 6% grasses.

**8.4 DISCUSSION**

**8.4.1 Sedimentology and chronology**

The poorly sorted sediments and high sand content suggest complex transport and depositional
energy regimes influence the sediment deposition into the Lielerai-Kimana wetland. The wet-
land is under high bioturbation pressure from microorganisms, herbivores and has a river running
<figure><img src="image_49.png" /></figure>

**Figure 5.** Relative abundance of the total pollen sum. Select taxa shown. Pollen groups based on qualitative predominance of taxa or structural growth forms in the Amboseli area (Githumbi *et al.* 2018a and 2018b; Rucina *et al.* 2010) with succulents shown in brackets. CONISS zonation with 1 statistically significant zone break and 1 insignificant zone bound between zone 2a and 2b (CONISS dendrogram units not shown; total sum of squares ×1000).
through the wetland that ephemerally floods. From the base of the core (384 cm) up to 100 cm, the sediments are characterised by moderate organic, high silt, and higher clay content. This could reflect the ephemeral nature of the catchment that is fed by a river with the headwaters in the nearby Kilimanjaro mountain. The low (<20%) organic content measured in the lower half of the core (384–200 cm; Figure 4) is similar to organic content measured from modern hip-popotamus pool margins, trails and mudflats inside the Ngorongoro Crater (Deocampo 2002); although, Ngorongoro crater wetlands are generally much larger and far less shaded by trees than is currently found at Lielerai-Kimana. In the uppermost unit (100 cm to the top; Figure 4), the magnetic susceptibility drops significantly, we observe a high Fe:Mn ratio, low Ti:Si ratio, high organic, charcoal and sand content. The radiocarbon ages suggest a high degree of remobilisation of organic content from within the catchment aged between 650–400 cal yr BP. It is frequently observed that organic matter (including charcoal after fires) and sands at the surface are transported by surface sheet wash during intense rain events on top of the very hard compacted soils (see also Shoemaker 2018, page 61). These materials could be transported into the riverine and palustrine features from the wider Amboseli landscape and trapped by vegetation (Courtney Mustaphi et al. 2015; Koff and Vandel 2008). Within the top 100 cm (Figure 3) the C/N values are very high and variable, indicative of terrestrial sources and the high variability may be due to certain layers, such as 30–50 cm and around 100 cm, having high rates of microbial activity.

Bulk sediment radiocarbon dates can produce older ¹⁴C dates because of aggregation of remobilised fine organic matter from the catchment and have a lower precision (Barnekow et al. 1998; Grimm et al. 2009). Bulk sediment offsets have not been explicitly investigated in wetland ecosystems in eastern Africa. The Lielerai-Kimana record at 101–100 cm provides one example of a comparison for a bulk sediment age estimate of 540 ± 24 (UBA-26122; Figure 3) and <63 µm sieved organic detritus age of 630 ± 35 (SUERC-64047). In this example, the age of the finer organic detritus was older than the total bulk sediment (with visible rootlets removed). In palustrine sediments, rootlet remains need to be avoided because of vertical movement of carbon in the stratigraphy. The offset could be due to a remainder of younger fine rootlets persisting in the bulk sediment sample, remobilised clay- and silt-sized organics in the catchment or remobilised organics with a variety of radiocarbon ages deposited together – with the limited comparable results, here it is difficult to discern the cause.

The distribution of the radiocarbon samples is less monotonic and not in stratigraphic superposition; but overall, there is a tendency towards older dates (1500–940 cal yr BP) towards the bottom of the core. The ²¹⁰Pb profile has some evidence of disturbed sediments over the past century, but is not completely mixed or noisy, and there are large offsets of around 400 years, between the ²¹⁰Pb and ¹⁴C radiometric dates. Offsets between radiocarbon dating of organic content and ²¹⁰Pb dating of the uppermost clastic sediments has been observed in sediments from temperature lacustrine deposits with the potential for remobilisation of older organic detritus in the catchment (Rinta et al. 2016). In nearby volcanic Crater Lake Duluti, Mount Meru, century-scale disparities between the ²¹⁰Pb age estimates and radiocarbon ages occurred in the top sediments (Öberg et al. 2012). This could be due to changing sedimentation from within the closed catchment of the crater due to land use and change cover change, and as varying water levels influencing the submerged macrophyte coverage and resuspension and deposition of organic sediments (Öberg et al. 2013).

The top of the record presented a reasonable curve of higher ²¹⁰Pb alpha radioactivities that decreased and reached a background activity by 34 cm depth; yet, the radioactivities suggest a slight some degree of sediment mixing from 23 to 7 cm (Figure 3A). The uppermost radiocarbon ages are several centuries older than the ²¹⁰Pb age estimates suggesting reworking of carbon from within the catchment for bulk and fine (<63 µm) organic matter. Potential causes include riverine overbank flow (wetland is located close to Kimana river), deposition of sediments and organic matter from the catchment, vegetation bioturbation through root establishment, and mammalian
bioturbation (the wetland is a key watering point for Amboseli wildlife and a Hippo pool). This may prevent centennial-scale interpretation of the palaeoenvironmental record. A combination of ²¹⁰Pb and radiocarbon dates at the top of our record improves the utility of the age-depth model by highlighting the influx of old and material. The proximity of Lielarai-Kimana wetland to Kimana River could be the main driver of the influx observed where flooding of the river and use of the wetland by the resident hippos is a constant source of sediment flow.

### 8.4.2 Regional palaeoenvironmental records

Several wetlands in the region have basal ages from 3000–1500 cal yr BP, suggesting a phase of wetland establishment and maintenance by hydroclimatic, topographical/geological (Liutkus and Ashley 2003; Owen et al. 2004), and biogeomorphological processes (Deocampo 2002; McCarthy et al. 1998). Palustrine sediments from the Amboseli and Tsavo areas have basal radiocarbon dates >5000 cal yr BP (Gillson 2004; Githumbi et al. 2018a; Rucina et al. 2010). Esambu had an older radiocarbon date of c. 5000 cal yr BP, and the sediments at this age were highly represented dry savannah pollen types, such as *Vachellia* (acacia) and *Amaranthaceae/Chenopodiaceae* as opposed to wetland taxa (Githumbi et al. 2018b). That suggests the landscape was an open patchy savannah where the lack of herbaceous vegetation or a continuous understory indicates a dry period and that the dimensions and spatial distribution of the hydric palustrine ecosystems within the semi-arid ecosystem varies through time in response to hydroclimatic, topographical, and biogeomorphological processes (Ashley et al. 2002, Casanova and Powling 2015; Jolly et al. 2008). Sediment cores collected from relatively small, montane wetlands in adjacent highland areas have similar basal ages (5000–1500 cal yr BP), including Kilimanjaro (Coetzee 1967; Courtney Mustaphi et al. 2020; Hamilton 1982), North Pare Mountains (Heckmann 2014), and Mount Shengena (Finch et al. 2017). The Late Holocene in this region was characterised by intermittent drought phases following the end of the African Humid Period (Verschuren et al. 2009) that influenced the vegetation and fire regimes of the savannas (Gillson 2004; Nelson et al. 2012; Urban et al. 2015). The stability of wetland vegetation has been described in coastal wetlands of eastern South Africa during the Late Holocene (Turner and Plater 2004).

### 8.4.3 Land-cover and land-use change

Semi-arid savannah and shrubland ecosystems of eastern African are characterised by high spatiotemporal variability in precipitation regimes that results in a diverse ecosystem composition, structure and distribution. The Amboseli landscape has undergone a series of land-use regimes through time and currently supports pastoralists, agriculture and wildlife. The dynamic nature of the Amboseli local ecosystem is shaped by these interactions between climate, ecosystem, herbivores and humans. Pollen, non-pollen palynomorph (NPP) and charcoal data from Esambu swamp indicated that sparse woodland and shrub taxa characterised the semi-arid Amboseli landscape from c. 5000–1700 cal yr BP (Githumbi et al. 2018b) with a change from a drier environment with a small aquatic areas that expanded as regional climates become moist. Several of the published archaeological records from Amboseli (Foley 1981; Shoemaker 2018) and Kilimanjaro area (Fosbrooke and Sassoon, 1965) also published radiocarbon ages during the late Holocene or ceramic wares dated to the Holocene and suggest extensive human land uses across Amboseli (Iles et al. 2018; Odner 1971). The ecosystem was occupied by hunter-gatherer groups and subsequent pastoral Neolithic communities with regionally archaeological evidence indicating a shift in livelihood strategies with specialised pastoralism emerging c. 3000 cal yr BP (Shoemaker 2018). The Namelok record, which covers the last c. 3000 cal yr BP, suggests the vegetation was a savannah mosaic dominated by acacias and *Amarathaceae/Chenopodiaceae*, *Asteraceae*, *Cissampelos*, *Poaceae* and *Salvadora* (Rucina et al. 2010). Pollen taxa recorded from
the Lielerai-Kimana record (Figure 5) concur with the other wetland records where the domi-
nant taxa include *Vachellia* (Acacia), Asteraceae, Amaranthaceae, *Commiphora*, *Balanites* and *Euphorbia*. The Lielerai-Kimana pollen taxa composition suggests that the landscape supported an open savannah shrubland over the last c. 1200 cal yr BP with most of the change experienced over the last c. 500 cal yr BP. This is evident from the charcoal record (Figure 4), which shows the continued presence of fires, and low biomass consuming fires until the last 500 years where the charcoal concentration and accumulation rate triple the mean values for the whole record. The Lielerai-Kimana record shows a mix of taxa that occur at low and high elevations including Afromontane taxa such as *Cordia*, *Podocarpus* and *Polyscias*. This suggests that Amboseli wet-lands record some of the wind-blown pollen from vegetation taxa on Kilimanjaro and Chyulu Hills.

During the Late Holocene, the Amboseli landscape has supported pastoralism and hunter-
gatherer livelihood strategies (Lane 2004). Caravan trade routes around Kilimanjaro penetrated
into Amboseli and the region was exploited for the ivory trade leading to high levels of defaunation
(Håkansson 2012); notably during the 1800s and 1900s driven by high ivory prices (Håkansson
2004). The 19th century droughts and disease epidemics decimated both livestock and wild
grazer populations in the region. To date, there has been no direct evidence in the archaeological
records of agriculture or combination livelihoods of agro-pastoralism in Amboseli during the Late
Holocene, although the absence of evidence is inconclusive and does not rule out the possibility
(Githumbi et al. 2018a; Shoemaker 2018). Land uses outside of parks has placed greater pressure
on protected areas as large herbivore populations increase in density. This concentration of
elephants in the parks has led to a decline in woody taxa in particular in smaller parks such
as Amboseli (Western et al. 2020). From the 1980s, conversion of the Amboseli wetlands for
subsistence and industrial food crop agriculture was the predominant land use change (Githumbi
et al. 2018b; MEMR 2012; Okello and Kioko 2011) outside of the national park.

Over the last c. 500 cal yr BP, significant changes are observed in the Amboseli ecosystem pollen, fire and geochemical records; the physiochemical signals indicate aridity interspersed with intervals of increased moisture, which could be increased local rainfall or increased water table levels caused by increased precipitation on Kilimanjaro and Chyulu. Namelok (Rucina et al. 2010) records a dry period from c. 500 cal yr BP indicated by the continuous presence and increase in taxa such as *Vachellia* (Acacia), Amaranthaceae/Chenopodiaceae, Cyperaceae and Poaceae. This is accompanied by a significant increase in charcoal levels attributed to presence of anthropogenic activity such as pastoralism and eventually agriculture at Lielerai-Kimana, Namelok and Esambu. Taxa associated with human activity are not identified from the Lielerai-Kimana record; however, *Ricinus communis* and *Cannabis sativa* are recorded with increasing numbers in Namelok from c. 1600 cal yr BP (Rucina et al. 2010). The Esambu wetland records a decrease in woody taxa with increasing Cyperaceae and Poaceae, a combination of a dry interval and human presence in the savannah and surrounding highlands. The decreased charcoal content in the top 20 cm ($^{210}$Pb dates of –38 cal yr BP) is consistent with the low occurrence of fires currently on the landscape observed by satellite observations (Githumbi et al. 2018a) and the high level of grazing pressure both by cattle and wild herbivores on the grazing-dominated savannahs (Bond and Keeley 2005; van Langevelde et al. 2003).

8.5 CONCLUSIONS

Small tropical wetlands provide information about the local changes in a landscape. However, they have to be utilised with caution on their own due to the inability to discern the driver or scale of ecosystem change. The Lielerai-Kimana wetland allows us to visualise the general Amboseli environment, i.e. a savannah shrubland and the changes within the wetland but not the drivers of the change. Data from Lielerai-Kimana, Esambu, Enkongu, Namelok wetlands highlight the
continued maintenance of a semi-arid savannah with varying levels of woodland. Significant social-ecological changes have occurred within the same interval that we observe the significant increase of charcoal c. 500 cal yr BP; arrival of the Maa-speaking pastoralists into Amboseli, widespread Swahili settlement increasing, arrival of the colonialist, increased elephant poaching and more recently land management policies. These past and current land cover and land use impacts and the timing of the vegetation, sedimentary and fire regime changes across the wetlands indicate localised controls; this emphasises the differential ecosystem responses of each wetland and highlights that small wetlands can be used to corroborate regional events.

## ACKNOWLEDGEMENTS

We thank Stephen Rucina, Veronica Muiruri, Rahab Kinyanjui and Rebecca Muriuki from the National Museums of Kenya, Palaeobotany and Palynology Section for field and laboratory support; Joseph Mutua and Nicholas Gakuu for fieldwork logistics; and the British Institute in Eastern Africa (Nairobi) for their continued support. We thank William Gosling, Anne-Marie Lezine and Louis Scott for their organisation of this special issue. This study contributes to the African Pollen Database (APD), Neotoma Paleoecology Database, and the PAGES supported Global Paleofire Working Group (GPWG2) and PAGES-LandCover6k. Past Global Changes (PAGES) is funded by the Swiss Academy of Sciences and Chinese Academy of Sciences and supported in-kind by the University of Bern, Switzerland. ENG and CCM were supported by a European Commission Marie Skłodowska-Curie Initial Training Network grant to RM and coordinated by Paul Lane through Uppsala University (FP7-PEOPLE-2013-ITN project number 606879). $^{210}$Pb and C/N data presented in this paper was supported by NERC Radiocarbon Allocation 1681.1012 or funded by the Natural Environment Research Council NERC standard grant number NE/I012915/1 to Dan Charman at University of Exeter, UK, and we thank Angela Gallego-Sala and the Millipeat Project. This research formed part of the PhD dissertation of EG, University of York. In memory of our friends and colleagues, Richard Payne and Eric Grimm.

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CHAPTER 9

# The new Garba Guracha palynological sequence: Revision and data expansion

Graciela Gil-Romera<fnref n="1" />, Mekbib Fekadu<fnref n="2" /> & Lars Opgenoorth

*Department of Ecology, Philipps-Marburg University, Marburg, Germany*

David Grady & Henry F. Lamb<fnref n="3" />

*Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, United Kingdom*

Lucas Bittner & Michael Zech

*Heisenberg Chair of Physical Geography, Technische Universität Dresden, Dresden, Germany*

Georg Miehe

*Department of Geography, Philipps-Marburg University, Marburg, Germany*

## 9.1 SITE DETAILS

In the context of the DFG-funded project ‘Mountain Exile Hypothesis’ (FOR2358) we retrieved a 15.5 m long sediment core from Garba Guracha (GG) (Bale Mountains National Park, Ethiopia – BMNP) during February 2017. A 16,000 year record of 62 pollen samples has been previously produced from GG by Umer *et al.* (2007). In this data paper, we present a new palynological and macrocharcoal record, with 259 pollen and 1301 charcoal samples covering the last 14 ka BP. Previous versions of the charcoal and *Erica* pollen records can be found in Gil-Romera *et al.* (2019). The depth-age model for the presented record in this new manuscript can be found in Bittner *et al.* 2020.

GG is a small (500 × 300 m), 6 m deep lake (6.9°N, 39.9°E), lying in a cirque at 3950 m asl in the BMNP of the Bale-Arsi Massif, Ethiopia (Figure 1). GG sits in a north-facing valley of the Sanetti plateau that was locally glaciated during the Last Glacial Maximum (Ossendorf *et al.* 2019; Tiercelin *et al.* 2008). High seasonality characterizes the rainfall pattern with a dry season from November to February and a bimodal wet season from March to October. Local rainfall patterns in BMNP present an altitudinal (lowlands to highlands) and latitudinal (N to S) increasing rainfall gradient, defining the vegetation zonation (Miehe and Miehe 1994). GG lies between the Ericaceous and afroalpine vegetation belts, however only dispersed *Erica* spp.

<footnote n="1">¹Other affiliation: *Department of Geoenvironmental Processes and Global Change, Pyrenean Institute of Ecology-CSIC, Zaragoza, Spain*</footnote>

<footnote n="2">²Other affiliation: *Department of Biology, Addis Ababa University, Addis Ababa, Ethiopia*</footnote>

<footnote n="3">³Other affiliation: *Department of Botany, Trinity College Dublin, Dublin, Ireland*</footnote>
<figure><img src="image_50.png" /><figcaption>**Figure 1.** Map of the study area (Bale Mountains National Park) situated east of the Ethiopian Rift Valley in Ethiopia, East Africa (made by Dr. Miguel Sevilla-Callejo). Layout of satellite image is from TerraMetrics© for Google Maps (2019).</figcaption></figure>

stands are present on the south east slopes of the catchment. The dominant plant communities around the lake consist of *Alchemilla haumannii* and *Helichrysum splendidum-H. citrispinum* shrublands. The northern lowland area has been heavily transformed by human activities and the natural vegetation remaining are dry fromontane forests dominated by *Podocarpus falcatus* and *Olea europaea* to 2700 m asl, followed by *Myrica salicifolia* and *Dodonaea viscosa* communities that give way at the upper forest limit to *Hagenia abyssinica-Juniperus procera* and *Schefflera* spp. communities up to 3200 m asl. *Erica trimera* and *E. arborea*, together with *Hypericum revolutum* form the Ericaceous belt found from 3200 m to 4000 m asl. The southern slopes receive rainfall throughout the year presenting a mixed broadleaved Fromontane rainforest dominated by *Pouteria aidssima*, *Ficus mucuso* but without *Juniperus* (Friis *et al.* 2010).

## 9.2 SEDIMENT DESCRIPTION AND METHODS

We retrieved two overlapping cores at 4.8 m water depth with a Livingstone corer from a raft. We obtained sediments to a maximum sediment depth of 1550 cm. Details of core retrieval, sedimentology and lithofacies can be found in Bittner *et al.* (2020). Charcoal particles and pollen data presented here cover from 13,700 to 94 cal. yr BP, as the bottom most sections were formed by highly inorganic sediments yielding counts too low to be statistically significant. Charcoal was sampled at contiguous intervals (1300 samples, Gil-Romera *et al.* 2019) and we analysed 259 pollen samples using a modified version of the laboratory protocol of Moore *et al.* (1994), adding *Lycopodium* spores (Lund University, batch # 1031, 15,636 spores per tablet, SD 592) to estimate concentration and pollen accumulation rates (PAR). A zonation was applied in order to facilitate the pollen data set interpretation. These pollen assemblage zones were done using a CONISS (Grimm 1987) cluster analysis. We calculated the Principal Curve (PrC) for our pollen assemblage to summarize the palynological compositional turnover along one ordination