Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-27T12:57:21.534Z Has data issue: false hasContentIssue false

Plant defence traits among discrete vegetation assemblages in a mesic savanna landscape in Kenya

Published online by Cambridge University Press:  26 May 2023

John Mbaluka Kimeu*
Affiliation:
Department of Biological Sciences, University of Cape Town, Rondebosch 7701, South Africa East Africa Herbarium, National Museums of Kenya, P.O Box 40658 – 00100, Nairobi, Kenya
Geoffrey Mwachala
Affiliation:
East Africa Herbarium, National Museums of Kenya, P.O Box 40658 – 00100, Nairobi, Kenya
Dawood Hattas
Affiliation:
Department of Biological Sciences, University of Cape Town, Rondebosch 7701, South Africa
Tammo Reichgelt
Affiliation:
Department of Geosciences, University of Connecticut, 354 Mansfield Road, Storrs, CT 06269, USA
A. Muthama Muasya
Affiliation:
Department of Biological Sciences, University of Cape Town, Rondebosch 7701, South Africa
*
Corresponding Author: John Mbaluka Kimeu; Email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

A trade-off between structural and chemical defences against herbivory in woody plants is alleged to depend on edaphic factors in African savannas. We studied anti-herbivory traits, in an edaphic mosaic of fertile and infertile soils within a savanna landscape in East Africa, towards elucidating herbivory defence traits expressions in woody plants of African savannas. We used data of 81 plants for 8 species from 8 sites — four sites from fertile soils (42 plants) and another four sites from infertile soils (39 plants). We did not find a general divide between structural and chemical strategies in our data. Instead, we found a range of defence traits combinations. Our results highlight that in woody plants of African savannas, chemical and structural defences can augment each other, and not necessarily trade-off. The diversity of herbivores, ranging from insects to mesobrowsers, may have driven the evolution of multiple defence strategies within the African savannas.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press

Introduction

Plants are primary producers in most ecosystems (Woodwell and Whittaker Reference Woodwell and Whittaker1968). It is therefore no surprising that one of the most prominent sets of adaptations in their life history is defence against natural enemies. Essentially, plants employ several different lines of defence strategies against herbivory, including structural (Hanley et al. Reference Hanley, Lamont, Fairbanks and Rafferty2007, War et al. Reference War, Taggar, Hussain, Taggar, Nair and Sharma2018) and chemical (War et al. Reference War, Taggar, Hussain, Taggar, Nair and Sharma2018) ones. Structural defence traits, such as leaf pubescence and leaf sclerophylly, affect herbivores by decreasing both palatability and digestibility (Hanley et al. Reference Hanley, Lamont, Fairbanks and Rafferty2007). Spinescence, another form of structural defence trait where parts of the plant shoot are modified into sharp tips, also affects herbivory by reducing feeding rates (Gowda Reference Gowda1996). Among the chemical defence types, tannins serve as a potent defensive secondary metabolite, as they bind proteins, inhibit enzymatic activity, and render protein present in a food nutritionally unavailable for herbivory (Mazid et al. Reference Mazid, Khan and Mohammad2011, Swain Reference Swain1977).

Until present, a trade-off between structural and chemical defences is alleged for fertile soil fine-leaved and infertile soil broad-leaved African savannas woody plants (Scholes and Walker, Reference Scholes and Walker2004). The basis for this hypothesised dichotomy is that African savannas fine-leaved woody plants, growing in nutrient-rich areas, tend to have high nutrient content leaves that are attractive to herbivores. As such, for the trees to defend themselves from intense herbivores browsing, they invest in structural defence strategy. Broad-leaved trees growing in nutrient-poor areas in African savanna landscapes, on the other hand, are purported to employ a chemical defence strategy (e.g., low leaf nutrient content and high secondary metabolites), which makes them unattractive to herbivores. Strong empirical support for a trade-off between the two defences (structural and chemical) in plants is however weakly reported in the field (see Moles et al. Reference Moles, Peco and Wallis2013).

In this study, using nutrient-rich and nutrient-poor soils common trees from a savanna landscape in Kenya, we further understanding of anti-herbivore traits dynamics in woody trees of African savannas. We test a support for the chemical and structural defences trade-off hypothesis in nutrient-rich versus -poor soils African savanna wood plants.

Materials and Methods

Description of study sites

The study was conducted at southeastern part of Kenya (0.67°S to 2.62°S, 37.70E° to 38.09°E; Figure 1a), in East Africa (Figure 1b). Study sites comprise a set of four sites from broad-leaved woody plant communities (Figure 1c), and another set of four sites from fine-leaved woody plant communities (Figure 1d). In the area, fine- and broad-leaved woody plant communities grow in relatively nutrient rich and nutrient poor soils, respectively (see Kimeu et al. Reference Kimeu, Mwachala, Reichgelt and Muasya2020). Domestic herds (largely goats) and small African mammalian browsers (e.g., dik-diks and antelopes) are the browsing ungulates predominant in the study vegetation. However, the vegetation is part of the larger East African savannas, which in the past formed one continuous ecosystem that harboured a large population of African mega-herbivores (Marchant et al. Reference Marchant, Richer, Boles, Capitani, Courtney-Mustaphi, Lane and Wright2018). The study vegetation is thus likely evolved in the presence of large densities of mega-herbivores, and perhaps under influence of fire — the other major disturbance to the vegetation in African savanna landscapes (see Bond Reference Bond2008, Sankaran et al. Reference Sankaran, Ratnam and Hanan2008 and also Midgley et al. Reference Midgley, Sawe, Abanyam, Hintsa and Gacheru2015).

Figure 1. Sampling sites and exemplar of vegetation types. (a) Location of fertile soil fine-leaved (circle, orange) and infertile broad-leaved (triangle, green) vegetation types, (b) position of study area in tropical Africa, (c) broad-leaved Combretum dominated woodlands, and (d) fine-leaved Acacia dominated woodlands.

Sampling strategy

We sampled woody plant species from eight sites — four sites from fertile soil fine-leaved Acacia dominated vegetation and another four sites from infertile soil broad-leaved Combretum dominated vegetation — for leaf samples. Sampling was conducted within a 2-week period in December 2019 to January 2020. Fully expanded mature leaves were sampled from three mature individuals (10 leaves per individual) of each study species at every site the species occurred. Only indigenous and the commonest woody species were sampled, and these include spiny Acacia and non-spiny Combretaceae species, which had previously showed to be the most dominant and frequent species to the study area (Kimeu et al. Reference Kimeu, Mwachala, Reichgelt and Muasya2020).

Plant traits measurement

Four leaf traits including specific leaf area (SLA), nitrogen (N), carbon (C), and condensed tannins (CTs) were measured. SLA index for every sample plant was calculated from averaged leaf areas and masses taken from a set of 10 mature and undamaged leaves collected per individual sample plant. Areas for the leaf samples were determined using the open-source software ImageJ (Abràmoff et al. Reference Abràmoff, Magalhães and Ram2004); and images used in the ImageJ encompassed a photograph of a whole leaf (i.e., including both petiole and rachis) photographed shortly after its collection (see Figure 2). The leaf weights were measured on air-dried leaf samples using a 0.01 gram digital electronic portable measuring scale. Leaf weighing was carried out at the University of Cape Town in the Biological Science department ecology laboratory.

Figure 2. (a–h) Representative leaf specimens of fertile soil Acacia woodland species (a) Acacia mellifera, (b) A. nilotica, (c) A. senegal, and (d) A. tortilis. (e–h) Representative leaf specimens of infertile soil Combretum woodland species (e) Combretum apiculatum, (f) C. collinum, (g) C. zeyheri, and (h) Terminalia brownii.

Measurement of leaf chemical traits used the same leaf samples examined for SLA. Specifically, the 10 leaves collected for each individual plant sample were pooled into one composite sample. Each composite was then mill ground to pass through a 2-mm sieve using a Hammer mill (United Scientific, Cape Town, USA). Leaf nitrogen (N) and carbon (C) contents were analysed using Thermo Scientific FLASH 2000 CHN Elemental Analyser (Thermo Fisher Scientific Inc., Massachusetts, USA). We used the protocol by Porter et al. (Reference Porter, Hrstich and Chan1986), as modified by Hagerman (Reference Hagerman2002), for quantifying CTs in plant samples leaves, and used purified Sorghum tannin as the protocol calibration standard (Hattas and Julkunen-Tiitto Reference Hattas and Julkunen-Tiitto2012).

Statistical analyses

To assess how well the predicted groups (nutrient-rich soils fine- and nutrient-poor soils broad-leaved woody plants) were able to assign each sample species to the correct group based on the sampled leaf traits (SLA, nitrogen, carbon, and CTs), we ran linear discriminant analysis (LDA) using the ‘Mass’ package in R. Further, we used the boxplot tool (in the R ‘stats’ package) to evaluate spread of values for the sampled leaf traits across the sample species. To test evidence for a trade-off in allocation to leaf traits associated with structural defence versus chemical defence for nutrient-rich soils, fine-leaved and nutrient-poor soils, broad-leaved woody species, we correlated SLA (which encompasses a plant’s sclerophylly index aspect) against each of the three sampled leaf chemical traits (nitrogen, carbon, and CTs). We used the ‘cor.test’ function of the R ‘stats’ package, and we plotted the plants for the groups in scatterplots spaces, with different symbols used for each group.

Results

A total of 81 plants (42 and 39 of from sites of Acacia dominated and Combretum dominated woody plant communities, respectively) were recorded for this study (Table 1 and Appendix 1).

Table 1. Commonest woody plant species in fertile soil fine-leaved and infertile soil broad-leaved plant communities at the mesic savanna of southeastern Kenya

Defences between fine-leaved and broad-leaved woody plant communities

LDA revealed 86.98% of variance of the studied leaf traits distributed along LDA1 (50.45%) and LD2 (36.53%). Fine-leaved, spinescent Acacia and broad-leaved, non-spinescent Combretaceae species loading along axis LDI were principally correlated with SLA and nitrogen, and along LD2 with carbon and CTs (Table 2).

Table 2. Coefficient of linear discriminants for the study leaf traits along axes LD1 and 2 derived from the study linear discriminant model.

When we compared measurements for each of the four sampled leaf traits between fine-leaved and broad-leaved plant functional groups, both SLA and leaf nitrogen differed markedly between the two plant groups. All fine-leaved spiny Acacia species had higher SLA than broad-leaved non-spiny Combretaceae species (Figure 3a). Fine-leaved spiny Acacia species again had generally higher leaf nitrogen content than Combretaceae species (Figure 3b). This pattern however was not repeated for leaf carbon and CTs — that is, both traits (carbon and CTs) had high and low peaks, which were species-specific rather than vegetation-type-specific (Figure 3c and d).

Figure 3. Boxplots showing SLA, leaf nitrogen, total carbon, and condensed tannin traits profiles for the common species (Acacia mellifera (A.me), A. nilotica (A.ni), A. senegal (A.se), A. tortilis (A.to), Combretum apiculatum (C.ap), C. collinum (C.co), C. zehyeri (C.ze), and Terminalia brownii (T.br)) of spiny, fine-leaved (orange) and non-spiny, broad-leaved (green) vegetation systems of the mesic savannas of southeastern Kenya.

Defence strategies trade-offs between fine- and broad-leaved woody plant communities

Despite some overlap, the current data revealed evidence for a trade-off of leaf nitrogen content profiles between Acacia and Combretaceae species (Figure 4a). The correlation coefficient for leaf nitrogen, between fine- and broad-leaved vegetation leaf categories, is significant (r = 0.67, p < 0.001). Carbon and CTs, however, did not show evidence of a trade-off between fine- and broad-leaved leaf samples, where the correlation coefficients recovered for carbon and CTs between fine- and broad-leaved vegetation leaf categories both are low and not significant (r = 0.12, p = 0.240 for carbon (Figure 4b), and r = 0.13, p = 0.210 for CTs (Figure 4c).

Figure 4. Pearson correlations of SLA plotted against leaf chemical traits nitrogen, carbon, and condensed tannins for spiny fine-leaved and non-spiny broad-leaved vegetation species of the mesic savanna of southeastern Kenya.

Discussion

This study set to test a trade-off between structural and chemical defence strategies alleged for fertile soil fine-leaved and infertile soil broad-leaved African savanna woody plants (Scholes and Walker Reference Scholes and Walker2004). The data presented here did not consistently support a trade-off between structural and chemical defence strategies in fertile soil fine-leaved and infertile soil broad-leaved woody plant samples. For example, results from the LDA showed that SLA and leaf nitrogen contributed the most to the first axis, while carbon and CTs contributed the most to the second axis, suggesting that there is no trade-off between the two traits sets in the studied vegetation systems. Had there been evidence for a strong trade-off between them, they would be expected to separate along a single axis. Furthermore, both leaf SLA and N indices were generally different between fertile soil fine-leaved and infertile soil broad-leaved plant samples, with a trend of higher quality (i.e., higher SLA and N) in fertile soil fine-leaved plant samples compared to the infertile soil broad-leaved plant samples). This trend however is not replicated for the other sampled two leaf traits (leaf carbon [C] and CTs).

The concept that chemical and structural defence syndromes can augment each other and do not necessarily trade-off has emanated from this work. This pattern is curious given that a previous work by Tomlinson et al. (Reference Tomlinson, van Langevelde, Ward, Prins, de Bie, Vosman, Sampaio and Sterck2016) reported a support for the Scholes and Walker (Reference Scholes and Walker2004) chemical and structural defences trade-off hypothesis in nutrient-rich versus -poor soils African savanna wood plants — although also there are other data that show in African savanna landscapes a section of spiny woody species growing in nutrient-rich soils could invest in chemical anti-herbivore defences equally to non-spiny broad-leaved plants growing in nutrient-poor soils (Wigley et al. Reference Wigley, Fritz and Coetsee2018, Reference Wigley, Coetsee, Augustine, Ratnam, Hattas and Sankaran2019). The current data perhaps is highlighting Agrawal (Reference Agrawal2011) intuition that a simple trade-off model is unlikely as multiple defence traits in concert would be more effective, that is, a diverse suite of herbivores with different responses to specific chemicals or defences may attack a particular species.

In the simple trade-off model, fine-leaved species should not invest in high-carbon concentration (Figure 3c), when fine-leaved species are assumed to be defended by structural defences rather chemical defences (Scholes and Walker Reference Scholes and Walker2004) — although carbon is also a critical structural element that provide biomechanical support for plant tissues (Niinemets and Tamm, Reference Niinemets and Tamm2005). It is also not clear why some fine-leaved species invest in high CTs (Figure 3d), and yet this is a trait expected in broad-leaved savanna trees in the simple trade-off model (see Scholes and Walker, Reference Scholes and Walker2004, and also Tomlinson et al., Reference Tomlinson, van Langevelde, Ward, Prins, de Bie, Vosman, Sampaio and Sterck2016). CT concentration has been shown to influence herbivores’ diet choice as it makes nutrients less available after ingesting (Ward and Young Reference Ward and Young2002, Scogings et al. Reference Scogings, Dziba and Gordon2004). Nonetheless, similar to our results, both low and high CTs indices have been previously reported by other studies focusing on fine-leaved spiny woody plant species in African savannas. In north-central Kenya, fine-leaved Acacia drepanolobium browsed by antelope and megaherbivores contained 1.0 to 17.1% CTs (Ward and Young Reference Ward and Young2002). Furthermore, in the same study area, A. etbaica and A. brevispica contained 1.3% and 20.8% CTs, respectively (Ford et al. Reference Ford, Goheen, Otieno, Bidner, Isbell, Palmer, Ward, Woodroffe and Pringle2014; Ward and Young Reference Ward and Young2002).

Aspects of phylogenetic history are known to shape expression of suites of defence traits in species, and especially when species are closely related (Agrawal and Fishbein Reference Agrawal and Fishbein2006). In the current study, for each vegetation type we sampled species from a singular family (Fabaceae and Combretaceae for fine- and broad-leaved vegetation types, respectively). While we take seriously the recognizant of a consequence of functional attributes having deep historical origins, we argue that the trait patterns recovered in our data cannot all be explained by biases due to phylogenetic signals. In the study area, for example, there are two Combretaceae species (Combretum aculeatum and Terminalia spinosa, see Kimeu et al. Reference Kimeu, Mwachala, Reichgelt and Muasya2020) with relatively fine-leaved and spines, but none of the sampled Combretaceae species here has these traits.

Overall, this study results have shown that plant anti-herbivory defences are complex, and perhaps operating in tandem. The dominant species in each vegetation type in the study showed the two defence strategies may overlap, for example, at least with some species combining structural defence strategy traits (nutritious leaves [high SLA and nitrogen]) with chemical defences (CTs and carbon). The results affirm the logical thought that it is inappropriate to follow a single line of defence in plants as plants themselves can employ multiple sets of defences (see Agrawal and Fishbein Reference Agrawal and Fishbein2006). Lastly and more importantly, our study greatly contributes to understanding plants’ herbivory niche partition that could account for the high herbivore diversity supported by wood species within landscapes of East Africa savannas (Appendix 1).

Acknowledgements

We thank Mr. Justus Kikuvi for assisting in data collection and the National Museums of Kenya and University of Cape Town (UCT) for infrastructural.

Financial support

Funds of this project are from the Francis H. Brown Fund (under the Leakey Foundation) and were provided to the first author of this work as postgraduate support.

Competing interest

The authors have declared that no competing interests exist, given that this study was not research commissioned by industry.

Publishing Ethics

This data and work are not plagiarised. However, the work is based on a chapter submitted towards a PhD by the first author of this article and with a permission from the other authors

Ethical statement

None.

Appendix 1

List of woody plants for the Acacia and Combretum plant communities’ common species alongside their respective four leaf traits

SLA, specific leaf area; N, nitrogen content; C, carbon content; and CTs, condensed tannins used for investigations of the trade-off between structural and chemical defences against herbivory phenomenon in African savanna woody plants.

References

Abràmoff, MD, Magalhães, PJ and Ram, SJ (2004) Image processing with ImageJ. Biophotonics International 11, 3642.Google Scholar
Agrawal, AA (2011) Current trends in the evolutionary ecology of plant defence. Functional Ecology 25, 420432.CrossRefGoogle Scholar
Agrawal, AA and Fishbein, M (2006) Plant defense syndromes. Ecology 87, 132149.CrossRefGoogle ScholarPubMed
Bond, WJ (2008) What limits trees in C4 grasslands and savannas? Annual Review 39, 641659.Google Scholar
Ford, AT, Goheen, JR, Otieno, TO, Bidner, L, Isbell, LA, Palmer, TM, Ward, D, Woodroffe, R and Pringle, RM (2014) Large carnivores make savanna tree communities less thorny. Science 346, 346349.CrossRefGoogle ScholarPubMed
Gowda, JH (1996) Spines of Acacia tortilis: what do they defend and how. Oikos 77, 000000.CrossRefGoogle Scholar
Hagerman, AE (2002) The tannin handbook. Available at: http://www.users.muohio.edu/hagermae.Google Scholar
Hanley, ME, Lamont, BB, Fairbanks, MM and Rafferty, CM (2007) Plant structural traits and their role in anti-herbivore defense. Perspectives in Plant Ecology, Evolution and Systematics 8, 157178.CrossRefGoogle Scholar
Hattas, D and Julkunen-Tiitto, R (2012) The quantification of condensed tannins in African savanna tree species. Phytochemistry Letters 5, 329334.CrossRefGoogle Scholar
Kimeu, JM, Mwachala, G, Reichgelt, T and Muasya, AM (2020) Characterization of alternative stable vegetation assemblages in a mesic savanna in Kenya. African Journal of Ecology 00, 111.Google Scholar
Marchant, R, Richer, S, Boles, O, Capitani, C, Courtney-Mustaphi, GJ, Lane, P and Wright, D (2018) Drivers and trajectories of land cover change in East Africa: human and environmental interactions from 6000 years ago to present. Earth-Science Reviews 178, 322378.CrossRefGoogle Scholar
Mazid, M, Khan, TA and Mohammad, F (2011) Role of secondary metabolites in defense mechanisms of plants. Biology and Medicine 3, 232249.Google Scholar
Midgley, JJ, Sawe, T, Abanyam, P, Hintsa, K and Gacheru, P (2015) Spinescent East African savannah acacias also have thick bark, suggesting they evolved under both an intense fire and herbivory regime. African Journal of Ecology 54, 118120.CrossRefGoogle Scholar
Moles, AT, Peco, B, Wallis, IR et al. (2013) Correlations between physical and chemical defences in plants: tradeoffs, syndromes, or just many different ways to skin a herbivorous cat? New Phytologist 198, 252263.CrossRefGoogle ScholarPubMed
Niinemets, Ü and Tamm, Ü (2005) Species differences in timing of leaf fall and foliage chemistry modify nutrient resorption efficiency in deciduous temperate forest stands. Tree Physiology 25, 10011014.CrossRefGoogle ScholarPubMed
Porter, LJ, Hrstich, LN and Chan, BC (1986) The conversion of procyanidins and prodelphinins to cyanidin and delphinin. Phytochemistry 25, 223230.CrossRefGoogle Scholar
Sankaran, M, Ratnam, J and Hanan, NP (2008) Woody cover in African savannas: the role of resources, fire and herbivory. Global Ecology and Biogeography 17, 236245.CrossRefGoogle Scholar
Scholes, RJ and Walker, BH (2004) An African Savanna: Synthesis of the Nylsvley Study. Cambridge: Cambridge University Press.Google Scholar
Scogings, P, Dziba, E and Gordon, IJ (2004) Leaf chemistry of woody plants in relation to season, canopy retention and goat browsing in a semi-arid subtropical savanna. Austral Ecology 29, 278286.CrossRefGoogle Scholar
Swain, T (1977) Secondary compounds as protective agents. Annual Review of Plant Physiology 28, 479501.CrossRefGoogle Scholar
Tomlinson, KW, van Langevelde, F, Ward, D, Prins, HHT, de Bie, S, Vosman, B, Sampaio, EVSB and Sterck, FJ (2016) Defence against vertebrate herbivores trades off into architectural and low nutrient strategies amongst savanna Fabaceae species. Ikos 000, 001011.Google Scholar
War, AR, Taggar, GK, Hussain, B, Taggar, MS, Nair, RM, Sharma, HC (2018) Plant defence against herbivory and insect adaptations. AoB PLANTS 10, ply037.Google Scholar
Ward, D and Young, TP (2002) Effects of large mammalian herbivores and ant symbionts on condensed tannins of Acacia drepanolobium in Kenya. Journal of Chemical Ecology 28, 921937.CrossRefGoogle ScholarPubMed
Wigley, BJ, Coetsee, C, Augustine, DJ, Ratnam, J, Hattas, D and Sankaran, M (2019) A thorny issue: Woody plant defense and growth in an East African savanna. Journal of Ecology 107, 18391851.CrossRefGoogle Scholar
Wigley, BJ, Fritz, H and Coetsee, C (2018) Defence strategies in African savanna trees. Oecologia 187, 797809.CrossRefGoogle ScholarPubMed
Woodwell, GM and Whittaker, RH (1968) Primary production in terrestrial ecosystems. American Zoologist 8, 1930.CrossRefGoogle Scholar
Figure 0

Figure 1. Sampling sites and exemplar of vegetation types. (a) Location of fertile soil fine-leaved (circle, orange) and infertile broad-leaved (triangle, green) vegetation types, (b) position of study area in tropical Africa, (c) broad-leaved Combretum dominated woodlands, and (d) fine-leaved Acacia dominated woodlands.

Figure 1

Figure 2. (a–h) Representative leaf specimens of fertile soil Acacia woodland species (a) Acacia mellifera, (b) A. nilotica, (c) A. senegal, and (d) A. tortilis. (e–h) Representative leaf specimens of infertile soil Combretum woodland species (e) Combretum apiculatum, (f) C. collinum, (g) C. zeyheri, and (h) Terminalia brownii.

Figure 2

Table 1. Commonest woody plant species in fertile soil fine-leaved and infertile soil broad-leaved plant communities at the mesic savanna of southeastern Kenya

Figure 3

Table 2. Coefficient of linear discriminants for the study leaf traits along axes LD1 and 2 derived from the study linear discriminant model.

Figure 4

Figure 3. Boxplots showing SLA, leaf nitrogen, total carbon, and condensed tannin traits profiles for the common species (Acacia mellifera (A.me), A. nilotica (A.ni), A. senegal (A.se), A. tortilis (A.to), Combretum apiculatum (C.ap), C. collinum (C.co), C. zehyeri (C.ze), and Terminalia brownii (T.br)) of spiny, fine-leaved (orange) and non-spiny, broad-leaved (green) vegetation systems of the mesic savannas of southeastern Kenya.

Figure 5

Figure 4. Pearson correlations of SLA plotted against leaf chemical traits nitrogen, carbon, and condensed tannins for spiny fine-leaved and non-spiny broad-leaved vegetation species of the mesic savanna of southeastern Kenya.