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Range size and dispersal of grasses (Poaceae) in Africa 

Aluoneswi Caroline Mashau 

 

 

 

 

 

 

 

 

 

 

 

A thesis submitted in partial fulfillment of the requirements for the 

degree of Doctor of Philosophy in the Faculty of Science, 

Department of Animal, Plant and Environmental Sciences, 

University of the Witwatersrand, Johannesburg, South Africa  

 

  



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DECLARATION 

I, Aluoneswi Caroline Mashau, declare that the thesis that I hereby submit for the 

degree Doctor of Philosophy at the University of the Witwatersrand, Johannesburg, 

is my own work and has not previously been submitted by me for a degree at this 

or any other university. 

 

 

 

 

 

Supervisor:  

Prof. Sally Archibald 

Dr Caroline E. R. Lehmann  

Dr Maria S. Vorontsova 

Dr Gareth P. Hempson 

 

 

University of the Witwatersrand, Johannesburg, South Africa 

 

 

 

Aluoneswi Caroline Mashau 

Date   29.05.2023 

  



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ABSTRACT  

 

Geographic range size is the outcome of both evolutionary and ecological processes. Therefore 

both historical contingencies, and the ecological characteristics (traits) of particular species, 

interact to result in observed distribution patterns. These distribution patterns are also changing – 

expanding as species invade into new ecosystems, and shrinking as species are filtered from 

ecosystems due to climate change or changing land management. Understanding current 

distributions and range sizes is therefore important for helping explain biogeographic patterns 

and processes, for informing conservation action, the management of invasive plants, and 

interventions to adapt to climate change. The grass family (Poaceae) covers approximately 31–

43% of the land surface globally, and started to spread during the Miocene period 

(approximately 8–20 Million years ago) to achieve its current dominance. This would have 

occurred through rapid range expansion as well as speciation and has resulted in some species 

with almost cosmopolitan (global) distributions, as well as rare grass species found in only a few 

localities. This study aims to understand the drivers of range size and dispersal traits of grasses in 

Africa with the purpose of quantifying differences between clades and functional types, and 

determine the floral traits that likely influence dispersal modes.  

 

In Chapter 1 I compiled general introduction of the whole thesis including background, 

rationale, aims and objectives. In Chapter 2 I aimed to understand the geographical distribution 

of grasses in sub-Saharan Africa with reference to key plant traits thought to affect range size in 

this family (Poaceae). Specifically, to test hypotheses on the importance of plant height and 

lifespan in determining range size and invasion potential in the context of their evolutionary 

history. The range sizes of 757 grass species native to southern Africa were estimated for the 

sub-Saharan African region from geo-referenced herbarium records using the alpha hull function. 

Phylogenetic generalised least squares models and linear mixed effects models were fitted to test 

whether grass range size was related to plant height and lifespan. Tribe-level relationships 

between range size and plant height were assessed with linear models. For species introduced to 

other continents, generalised linear mixed effects models were fitted to test whether invasiveness 

was related to native range size, plant height and lifespan. Differences in native range size 



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among species in four invasion-related categories were assessed with linear mixed effects 

models. Geographic range sizes were larger for taller grass species and for species with shorter 

lifespans. The relationship between plant height and range size varies widely among tribes, with 

some environmentally-restricted tribes not showing significant responses to plant height. Grasses 

with larger native range sizes and shorter lifespans are more likely to become invasive after 

being introduced to other continents. Grass species introduced to other continents have larger 

native range sizes than those that have not, and native range size increases along the introduced-

naturalised-invasive continuum. The increased dispersal opportunities of annual-biannual grasses 

appears to have a greater positive effect on range size than do the longer generation times of 

perennial grasses. Grass height has and continues to be an important driver of grass 

biogeography, with implications for understanding the spread of certain grass tribes over the 

Miocene. Factors that promote large native range sizes are also likely to increase the probability 

of a species becoming invasive. 

 

Grass floral structures vary greatly but we have very little understanding of their functional 

significance. Due to the varied dispersal mechanisms shown by grasses, certain syndromes of 

floral traits would likely be associated with particular strategies for dispersal, and consequently, 

different environments. In particular, effective seed maturation and dispersal in fire-prone tall 

grasslands would require different floral trait syndromes than in short, frequently grazed 

ecosystems. In Chapter 3 I quantified floral traits of nearly 200 Poaceae species from savanna 

and grassland ecosystems in southern Africa and explored how their floral structures co-vary and 

correlate with other functional characteristics such as grass height. Using field information on the 

dominance disturbance regime of 163 of these grass species it was tested whether certain floral 

traits are more associated with fire vs grazing. Non-metric multi-dimensional scaling (NMDS) 

was used to illustrate how floral traits covaried among grass species, and to group them into 

syndromes based on these traits. Analysis of variance (ANOVA) was used to test whether certain 

floral trait syndromes were more associated with fire vs grazing. I identified four clear floral trait 

syndromes separated largely by awn length and the presence of hooks/prickles or bristles. Long-

awned species were more likely to be found in frequently burned environments and were also 

usually taller than species without awns. Grazer-dominated systems appear to select for two 

different floral trait syndromes. The study has improved our ecological and taxonomic 



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understanding of how floral traits differ among the range of tribes in one family across African 

countries. It can help in understanding dispersal limitations in grasses and predicting which 

species are likely to flourish in particular grassland habitats.  

 

The grass family (Poaceae), despite having only emerged and spread in the last 50 million years, 

is cosmopolitan, and many species have large, almost cosmopolitan distributions. Lineage age 

and dispersal ability are two factors thought to explain the variation of range size and grasses 

show a wide range of floral structures and heights associated with different dispersal strategies. 

In Chapter 4 I aimed to assess how dispersal syndrome (inferred from floral structures and other 

functional traits) and evolutionary history affect range size in the grass subtribe Eleusininae – a 

tropical grass clade with variation in floral structures. Global location records for 97 grass 

species of 29 Eleusininae genera were used to quantify range size, and linear models were used 

to test the relationship between range size and interaction between plant height, and lemma awn 

state (absent/present), caryopsis length (mm) and genus age. Taller grass species with awned 

lemmas were found to have a larger range size, and this supports my hypothesis (developed in 

Chapter 2) that the importance of grass height in driving range size depends on the dispersal 

syndrome. It was found that there is no relationship between genus age versus floral and 

functional traits used in this analysis. The study can help to explain some of the differences in 

biogeographic history between different lineages and also determine dispersal syndromes. 

 

In Chapter 5 I compiled general discuss or overview of the study, including geographical 

distribution of the southern African grasses, grass clades co-vary according to their floral traits, 

conservation and management implications, limitations of this study and needs for future 

research and conclusion. 

  



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DEDICATION 

I dedicate this thesis to my husband, Fulufhelo Mashau and my children Tsiko, 

Huwelelani and Rovhidzwa Mashau 

Thank you for support and words of encouragement. 

  



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ACKNOWLEDGEMENTS 

 

The research project expenses were covered by the South African National Biodiversity Institute 

(SANBI) for paid University tuition fees, and other funds were from Newton Advanced 

Fellowship (NA17095) and a Royal Society International Collaboration Award (IC170015). The 

University of Witwatersrand and South African National Biodiversity Institute (SANBI) are 

thanked for their support and all funders for making this research possible.  

I would like to say a big thanks to my supervisor Prof. Sally Archibald and co-supervisors Dr 

Caroline E. R. Lehmann, Dr Maria S. Vorontsova and Dr Gareth P. Hempson for making my 

dream come true, giving me support and encouragement and believing in me. A special word of 

thanks to all co-authors Dr Vernon Visser, Dr Abraham Dabengwa, Dr Cedrique L. 

Solofondranohatra and Dr Watchara Arthan for contributing to three valued papers of this 

research study. Thank you Ms Thando Caroline Twala (University of Witwatersrand) for 

assistance in the R-studio programme, Dr Jan Hackel (RGB Kew) for merging a recent grass 

phylogenetic tree with the list of grass genera found in southern Africa. 

Thank you to South African National Biodiversity Institute (SANBI) colleagues for supporting 

and listening to my problems now and then, especially the late Dr Elizabeth Retief. Former 

SANBI supervisor, Dr Jacques van Rooy, thanks for consistent mentoring, guidance and support. 

A special word of thanks to Mrs Nicole L. Meyer for editing this thesis and Ms Sandra Turck for 

designing the illustrations plate. 

Lyn Fish (former Poaceae specialist) who showed me love and support that cannot be overstated, 

and acted like a mother, teacher, mentor, adviser and finally a granny to my children. Special 

thanks to my husband Mr Fulufhelo Mashau for being an understanding person and my children, 

Tsiko, Huwelelani and Rovhidzwa Mashau for such support, and even being an inspiration to 

me. Finally thanks to my wonderful mother Aifheli Sarah and my late dad Ntsundeni Jack 

Mudau for bringing me onto this earth.  

  



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TABLE OF CONTENTS 

DECLARATION………………………………………………….….…………………………...2 

ABSTRACT………………………………….……………………………………………………3 

DEDICATION…………………………………………………………….………………………6 

ACKNOWLEDGEMENTS……………………………………………………………………….7 

LIST OF FIGURES………………………………………………..…….……..……………..…11 

LIST OF TABLES………………………………………………………………………………17 

Chapter 1 | General introduction………………………………………………………...……18 

1.1 Background………………………………………………………………………….……….19 

1.1.1 The value and potential of using taxonomic resources to explore ecological questions…..19 

1.1.2 Range size or spatial distribution………………….…………………………………….....20 

1.1.3 Grass dispersal modes…………………………………………………………………..….21 

1.2 Rationale…………………………………………………………………………….……….22 

1.3 Aims and objectives……………………………………………………..…………………...23 

Chapter 2 | Plant height and lifespan predict range size in southern African grasses……..25 

2.1 | Abstract…………………………………………………………………………..…………26 

2.2 | Introduction……………………………………………………………..……………....…..28 

2.3 | Materials and Methods………………………………………...……………………..……..33 

2.3.1 Species occurrence data and mapping……………………………………….…………….33 

2.3.2 Species trait data………………………………………………………..…………...……..34 

2.3.3 Range size calculations…………………………………………………………………….34 

2.3.4 Grass phylogeny……………………………………………………………………………36 

2.3.5 Statistical analyses…………………………………………………………………………36 

2.3.5.1 Phylogenetically controlled analysis of range size……………………………..…..……36 

2.3.5.2 Range size analysis for the full species dataset……………………………………….....36 

2.3.5.3 Tribe level range size vs plant height relationships……………………………………...37 

2.3.5.4 Range size as a predictor of invasiveness…………….………………………………….37 

2.4 | Results…………………………………………………………………………..…………..38 



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2.4.1 Phylogenetically controlled analysis of range size……………………………………..….39 

2.4.2 Range size analysis for the full species dataset………………………………………...….39 

2.4.3 Tribe level range size vs plant height relationships…………………………………..……40 

2.4.4 Range size as a predictor of invasiveness……………………………………….………....41 

2.5 | Discussion………………………………………………………………………..…….…...44 

2.6 | Conclusion………………………………………………………….…………………..…..47 

Chapter 3 | Floral trait syndromes in tropical grasses and their environmental 

associations…………………………………………………………………………….………..48 

3.1 | Abstract……………………………………………………………….…………...…..……49 

3.2 | Introduction…………………………………………………………….…………….……..50 

3.3 | Materials and Methods…………………………………..………………………..…….…..54 

3.3.1 Classifying species as fire, grazing or intermediate environment……………….…..….…54 

3.3.2 Quantifying floral traits …………………………………………………………………....55 

3.3.3 Statistical analysis …………………………………………..………………………….….57 

3.3.3.1 Clusters of grass species into floral trait syndromes ………………..…………...………57 

3.3.3.2 Dimensions of variation in floral traits……………………………….………….....……57 

3.3.3.3 Associations between floral trait syndromes, dominance disturbance regime and 

phylogenetic relationships...………………………………………….….………………………57 

3.4 | Results…………………………………………………………..…………………………..58 

3.4.1 Groups of grasses with similar “floral trait syndromes” (clustering)…………………..….58 

3.4.2 Dimensions of variation in floral traits…………………………………………………….60 

3.4.3 Associations between floral trait syndromes, dominance disturbance regime and 

phylogenetic relationships…………………..………………………………….………………..63 

3.5 | Discussion……………………………………………………………….…..……………...67 

3.6 | Conclusion……………………………………………………………………..………..….71 

Chapter 4 | Do dispersal syndromes and evolutionary history determine the range size of 

the subtribe Eleusininae (Poaceae: Chloridoideae: Cynodonteae) 

worldwide?………………………………………………………………………………………72 

4.1 | Abstract…………………………………………………………………………………..…73 

4.2 | Introduction………………………………..………………………………………………..74 



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4.3 | Materials and Methods………………………………………….…………………………..77 

4.3.1 Identifying an appropriate grass clade and genus age……………………….…………….77 

4.3.2 Plant traits data and species location records……………......……..…..…………………..78 

4.3.3 Calculating range size ………………………………………………………………….….79 

4.3.4 Statistical analysis …………………………………………………………………………80 

4.4 | Results……………………………………………………………………..………………..81 

4.4.1 Evolutionary history of the grass genera under the subtribe Eleusininae………...………..81 

4.4.2 Correlation between lemma awn state versus height, genus age and 

caryopsis……………………………………………………………………………………..…..81 

4.4.3 Test whether the relationship between range size and plant height depends on lifespan, 

lemma awn state, caryopsis and genus age………………………….…………………………...83 

4.5 | Discussion……………………………………….…………..………………………….…..85 

4.6 | Conclusion……………………………………………….…………………..……………..88 

Chapter 5 | General discussion………………………………………………………………...89 

5.1 | General overview of the study……………………………………………………...………90 

5.1.1 Geographical distribution of the southern African grasses…………………………….…..91 

5.1.2 Grass clades co-vary according to their floral traits…………………………...…………..93 

5.1.3 Conservation and management implications……..………………………………………..94 

5.1.4 Limitations of this study and needs for future research……………………………......…..95 

5.2 Conclusion……………………………………………………………………………...……97 

REFERENCES………………………………………………………………………..……..…..98 

Appendix A………………………………………………………………………………..……116 

Appendix B…………………………………………………………………..…………………129 

Appendix C……………………………………………………………….…………………….136 

  



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LIST OF FIGURES 
 

Figure 2.1. Conceptual diagram showing the various mechanisms by which grass height and 

lifespan could affect range size. Solid lines represent positive relationships and dashed 

lines represent negative relationships. Plant height can increase range size by increasing 

dispersal potential, but decrease it through reduced relative reproductive output and thus 

reduced dispersal opportunities. Likewise, plant height increases competitive ability, 

which increases establishment success and can lead to larger range sizes, but long 

generation times and slow mutation rates will increase genetic isolation and promote 

speciation, which results in smaller range sizes. Moreover, short-lived plants are expected 

to have larger range sizes because they have higher reproductive output and dispersal 

potential, but they also have low competitive ability and short generation times, which 

might decrease establishment success and increase genetic isolation and speciation 

respectively, resulting in an overall lower range size. Therefore, the slope of the 

relationship between plant height, lifespan and range size helps to determine which of 

these processes is more important for explaining patterns in the grass family. These are 

not the only traits or mechanisms affecting range size; for a comprehensive discussion, 

please see Sheth et al. (2020).  

Figure 2.2. Map of the study area showing the number of GBIF records for Poaceae per quarter 

degree grid square, which provides an indication of the variation in sampling effort across 

the continent. The 757 species assessed in this study are all native to the region occupied 

by the five southern African countries outlined in black, however, their range sizes were 

calculated for the entire sub-Saharan Africa region including Madagascar. 

Figure 2.3. Histogram of the range sizes (km2, log-scale) of southern African grasses, estimated 

using the alpha hull method with alpha = 200 km. Tribe-level range size distributions are 

indicated by stacked colour bands. 

Figure 2.4. Relationships between range size (km2, log-scale) and plant height (mm, log-scale) 

for 757 southern African grasses with annual-biannual (open symbols and dashed line) or 

perennial (solid symbols and line) lifespans, as estimated by a linear mixed effects model. 



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Genus nested within tribe was fitted as a random intercept term in the model to partially 

account for evolutionary constraints. 

Figure 2.5. Tribe-level relationships between range size (km2, log-scale) and plant height (mm, 

log-scale) and plant lifespan (annual-biannual vs. perennial) for 757 species in 144 

genera and 12 tribes of southern African grasses. Linear models were fitted to species 

range size data for each tribe separately, with height fitted as a predictor in all models, 

and lifespan fitted where annual-biannual and perennial categories were represented by 

five or more species each. Solid lines represent a significant effect of plant height, and 

dashed lines represent a non-significant effect of plant height; shaded areas represent the 

95% confidence interval for height parameter estimates. Red lines and shading represent 

annual-biannual species, blue represents perennial species, and black lines with grey 

shading represent all lifespans. The significance of lifespan effects on range sizes are 

indicated in each panel (“A-B vs. P” = annual-biannual vs. perennial), where *** = p < 

0.001, * = p < 0.05 and NS = p > 0.05. The photosynthetic pathways (i.e. C3 and/or C4) 

occurring in each tribe is shown in brackets after the tribe name. 

Figure 2.6. Probability of South African grasses becoming invasive following introduction to 

other continents as a function of their native range size in sub-Saharan Africa (km2, log-

scale) and lifespan (annual-biannual: open symbols and dashed line, or perennial: solid 

symbols and line). Probabilities were estimated by fitting a binomial generalised linear 

mixed effects model fitted to data for 250 grasses categorised as invasive (1) or 

introduced or naturalised (0) following Visser et al. (2016). Tribe was fitted as a random 

intercept in the model. 

Figure 2.7. Boxplot showing variation in native range sizes among 757 southern African grasses 

after classification into four invasion status categories: 1) not introduced to other 

continents, 2) introduced (but not [yet] naturalised or invasive), 3) naturalised (i.e. 

introduced and now naturalised but not [yet] invasive), and 4) invasive (i.e. introduced, 

naturalised and now invasive). Differences in range size among invasion categories were 

assessed using a linear mixed effects model, with genus nested within tribe fitted as a 

random effect. Categories with different letters are significantly different (p < 0.05). 



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Figure 3.1. Conceptual diagram based on the information from the literature about which floral 

traits are associated with each dispersal syndrome. Also shown are leaf and growth form 

functional traits that would be expected also to be associated with particular dispersal 

syndromes. Plant height and floral traits can function together to influence dispersal 

mode (either wind, epizoochory or endozoochory) and also to change the ecosystem 

community in a different environment.  

Figure 3.2. Dendrogram plot of hierarchical clustering of 163 grass species grouped based on 

similar floral trait syndromes, group A (in red colour), group B (in blue colour), group C 

(in green colour) and group D (in black colour). 

Figure 3.3. Non-metric multi-dimensional scaling (NMDS) ordination of grass species in two-

dimensional space based on six floral traits (lemma awn action, callus sharpness, lemma 

awn length and fertile spikelet length, dispersal unit and hooks/prickles). Orthogonal axes 

of trait variation are indicated by arrows representing directions of increase in trait 

values. Also shown is the hierarchical clustering of the four main groups projected onto 

the NMDS. *Note: Species abbreviations are used – full names can be found in Appendix 

B, Figure S3.6. The species abbreviations are formed by the first three letters of the genus 

name and plus the first three letters of the specific epithet. Some species are not 

represented in biplot to reduce overlap and increase clarity. 

Figure 3.4. Different grass flowering structures according to the clustering groups, A) long 

active lemma awn and sharp callus (Fish et al., 2015; Artists: S. B. Chiliza, M. Franks, 

W. Roux, C. Smith); B) passive lemma awns and a blunt callus (Fish et al., 2015; Artists: 

S. B. Chiliza, W. Roux, M. Ueckermann); C) no lemma awns, blunt or no callus 

sharpness (Fish et al., 2015; Artists: S. B. Chiliza, C. Letty, W. Roux); and D) 

hooks/prickles or bristles and no callus sharpness (Fish et al., 2015; Artists: S. B. Chiliza, 

B. Connell, M. E. Connell, G.E. Lawrence, C. Smith). Overall species per Group A = 34, 

Group B = 24, Group C = 94 and Group D = 11. 

Figure 3.5. Boxplots show the relationship between floral traits among four clustering groups, 

A) lemma awn length, B) fertile spikelet length, C) callus sharpness, D) awn action and 

E) hooks/ prickles vs clustering groups were significant (p < 0.001); F) dispersal unit vs 



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clustering groups was not significant (p =0.322). Four clustering groups are: Group A: 

long active lemma awn and sharp callus, Group B: passive lemma awns and a blunt 

callus, Group C: no lemma awns, blunt or no callus sharpness, and Group D: 

hooks/prickles and no callus sharpness. 

Figure 3.6. The associations between dominance disturbance regime of 163 species (fire, 

intermediate or grazing environment) and clustering groups. Four clustering groups are: 

Group A: long active lemma awn and sharp callus, Group B: passive lemma awns and a 

blunt callus, Group C: no lemma awns, blunt or no callus sharpness, and Group D: 

hooks/prickles and no callus sharpness. The clustering Group A and B are dominated by 

fire grasses, whereas Group C and D are dominated by grazing grasses. 

Figure 3.7. Boxplots showing how (A) lemma awn length and (B) fertile spikelet length varies 

in relation to the environment the grasses are generally found in. Grazing grasses have 

significantly (AOV P = 0.001) shorter awns than fire grasses. However, there is no 

difference in their spikelet lengths (AOV P = 0.193). 

Figure 3.8. Graph showing the associations between 163 grass species in 14 tribes and clustering 

of groups. The clustering Group A is dominated by Andropogoneae Group B is 

dominated by Cynodonteae and Group C and D are dominated by the Paniceae tribe. 

Figure 3.9. Tribe random effect intercept estimates from the linear mixed effect model, which 

assessed lemma awn length in response to plant height. The model was fitted to data for 

67 long lemma awn grass species representing 10 tribes in African countries. Tribe 

Andropogoneae, Aristideae and Tristachydeae had an intercept > 0.0, whereas 

Arundineae, Eragrostideae and Paniceae, Poeae and Triraphideae had an intercept < 0.0, 

while intercept estimates for Brachypodieae and Cynodonteae overlapped zero. 

Figure 3.10. The tribes fitted as a random effect, which assessed log lemma awn length (mm) in 

response to log of seed mass (g). The model was fitted to data for 38 grass species 

representing 6 tribes in African countries. Three tribes Andropogoneae, Aristideae and 

Tristachydeae had longer lemma awns and large seeds, whereas Cynodonteae, 

Eragrostideae and Paniceae tribes had short lemma awns and small seeds. 



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Figure 4.1. The phylogeny by Hackel et al. (2018) merged with the 97 grass species from 29 

genera in the subtribe Eleusininae. There was only DNA data for 33 species in 19 genera; 

the other species were given the genus age. The phylogenetic tree indicates that the 

current species have a range of ages, that awns are ancestral characters in the Eleusininae, 

and that species without awns have evolved several times. Therefore, this is an 

appropriate subtribe to test the hypotheses about the importance of dispersal mode and 

genus age on range size. 

Figure 4.2. Boxplots show the relationship between lemma awn state (absent= 0 and present=1) 

among three functional and floral traits, A) grass species with awned lemmas tended to 

have a large caryopsis/grain (these floral traits show a significant positive relationship 

with lemma awn state where p < 0.001); B) there was no relationship with height(p = 

0.655); C) genus age shows a slight difference in the species with lemma awn 

present/absent (p< 0.001).   

Figure 4.3. Correlation relationships between range size (km2, log-scale) and plant height (mm, 

log-scale) for 97 grass species in the subtribe Eleusininae globally with lemma awn state, 

awn present (solid symbols and line) or awn absent (light symbols and dash line). The 

shaded areas represent the 95% confidence interval for plant height and lemma awn state 

coefficient estimates. 

Figure 4.4. Correlation relationships between range size (km2, log-scale) and plant height (mm, 

log-scale) for 97 grass species in the subtribe Eleusininae globally: the linear model was 

run on continuous caryopsis (mm, log scale) data, but for visualisation I plotted the 

response to the mean size, as well as the mean+-1 standard deviation. The relationship 

with height does not vary with caryopsis size. The shaded areas represent the 95% 

confidence interval for plant height and log caryopsis coefficient estimates. 

Figure 4.5. Correlation relationships between range size (km2, log-scale) and log genus age 

(million years ago) of the 97 grass species of 29 genera, shows that there is no significant 

relationship between these two variables. The shaded areas represent the 95% confidence 

interval for the range size and log genus age coefficient estimates (coefficient = -0.817, p-

value = 0.199). Many species have the same age because they could only be assigned a 

genus age. This might limit the strength and power of the analysis. 



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Figure 5.1 From Visser et al. (2012); Figure 2. Predicted distribution of species richness for the 

four major C4 grass clades. Darker colours represent a high number of species for a 

particular clade in South Africa.   



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LIST OF TABLES 

 

Table 3.1. Indication of how grass floral traits were measured and their ecological functions 

(especially in relation to dispersal in a fire versus grazing environment). 

Table 4.1 Normal linear model was fitted to test range size (km2, log-scale) estimated using 

alpha values of 200 km, log height (mm), lemma awn state (absent = 0/present = 1), log 

caryopsis (mm), lifespan (two-level factor: “annual-biannual” or “perennial”) and genus 

age data for 97 grass species of the subtribe Eleusininae globally. This model includes an 

interaction between plant height and lemma awn state. Because the response variable was 

not normal, the P-value here reports on the results of a randomisation test: it represents 

the proportion of times that the true parameter was different from a parameter produced 

with a randomised dataset. 

 

  



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Chapter 1 | General introduction 

 

Background, rationale, aims and objectives 

  



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1 | General Introduction 

 

1.1 Background 

The Poaceae or Gramineae grass family is the fifth largest plant family worldwide, ranking 

behind only Asteraceae, Fabaceae, Orchidaceae and Rubiaceae in number of species. There are 

about 700 genera worldwide and approximately 11 000 grass species (Clayton et al., 2015), but 

southern Africa is represented by ± 978 species in ± 200 genera (Fish et al., 2015). Grasses 

started evolving at least in the late Cretaceous or Paleocene and occurred at or after 55–70 

million years ago and achieved their worldwide distribution due to long-distance dispersal 

mechanisms (Christin et al., 2014), and through harnessing fire and grazing to create appropriate 

habitat (Linder et al., 2018). Poaceae is the dominant vegetation in the tropics, Arctic and 

Antarctic areas and occurs in all habitats including swamps, deserts, forests, mountain tops and 

seashores. Ecosystems dominated by Poaceae cover almost 31–43% of the land surface (Gibson, 

2009; Linder et al., 2018; Archibald et al., 2019). It is therefore an important family, both 

ecologically and economically. Grasses are cultivated especially as food for humans and animals. 

In fact, they are the major source of all our food (grains and fodder for livestock) (Strömberg, 

2005; Fish et al., 2015; Linder et al., 2018). Grasses are also cultivated for lawns and erosion 

control, as well as garden ornamentals (Van Oudtshoorn, 2014; Fish et al., 2015).  

 

1.1.1 The value and potential of using taxonomic resources to explore ecological questions  

Increasingly, researchers are realizing the potential of using taxonomic data for asking ecological 

questions. Some of the main herbaria house several hundreds of thousands of plant vouchers 

from across the globe, and these are increasingly being digitized and converted into formats that 

are accessible for researchers from other disciplines to use. The geolocation data and detailed 

information on plant characters that are provided by classic taxonomic vouchering approaches 

provide information at large spatial scales; and linking these functional traits with data on the 

evolutionary history and phylogenetics of different plant groups enables important biogeographic 

and ecological questions to be asked.  

 

South African National Biodiversity Institute (SANBI, https://www.sanbi.org/) conducts 

nationwide biodiversity conservation assessments of various plants and animals, which involve 



20 
 

field trips for the collection data. Data on the identified and occurrence of South African grasses 

have been compiled at the SANBI herbarium by G.E. Gibbs Russell, L. Watson, M. Koekemoer, 

N.P. Barker, H.M. Anderson, M.J. Dallwitz, L. Fish (Smook), A.C. Mashau, M.J. Moeaha and 

M.T. Nembudani between 1980’s–2015 (Gibbs Russell et al. 1990; Fish et al., 2015). A 

biodiversity knowledge and information management system by SANBI integrated with the 

existing information resources of database such as Botanical Database of southern Africa 

(BODATSA/BRAHMS) (BODATSA, 2019) and Global Biodiversity Information Facility 

(GBIF.org, 2019) which can be access by both internal and external users. Kew Royal Botanic 

Garden, UK integrated their biodiversity information to Plants of the World Online (POWO, 

2019) and GrassBase (Clayton et al., 2015) which are freely accessible.  

 

1.1.2 Range size or spatial distribution 

Range size is a measure of the size of the geographical area (Brown et al., 1996; Gaston, 2003; 

Morueta-Holme et al., 2013, Sheth et al., 2020) where the species occurs. Geographic range size 

can change through time due to the evolutionary and ecological characteristics of a species 

(Gaston & Fuller, 2009). Due to human impact, organismal range sizes are changing, and 

assessing current range size, and its drivers, is important for assessing extinction risk and 

adaptation capacity (Manne et al., 1999; Staude et al., 2020). Moreover, invasion is the process 

of increasing range size and understanding and managing invasions requires understanding the 

factors constraining range size. Once a species is introduced, factors shaping plant reproduction 

and dispersal characteristics are likely as important as habitat suitability and establishment 

success in determining whether a species will become invasive (Pyšek et al., 2009). 

 

Taller plant species have a larger dispersal potential (Thomson et al., 2011), and are therefore 

more likely to expand their range by encountering new suitable habitats (Murray et al., 2002; 

Kristiansen et al., 2009). However, there is evidence that the importance of plant height in 

driving dispersal also depends on the dispersal mode employed (Thomson et al., 2011). As well 

as affecting dispersal, plant height also increases competitive ability, which increases 

establishment success and can lead to larger range sizes, as can long generation times, but can 

slower mutation rates associated with tall plants (Lanfear et al., 2013) will increase genetic 

isolation and promote speciation, and will result in smaller range sizes (Sheth et al. 2020). 



21 
 

Understanding the emergent effects of these sometimes counter-acting processes is key to 

explaining the drivers of range size. Finally, a recent meta-analysis by Sheth et al. (2020) of the 

factors predicting geographic range size in plants showed niche breadth (habitat suitability) to be 

consistently important. A plant can have a large range size but still not be dominant in any of the 

environments that it occurs in. Whether plants with large ranges are also the dominant species in 

their environments is therefore an interesting question – and would imply a correlation between 

the ecological factors promoting large range size and competitive ability.  

 

Plant lifespan is an independent factor that affects range size through impacts on reproduction 

and establishment. Annual-biannual grass species have higher reproductive allocation than 

perennial grasses (Wilson & Thompson, 1989; Vico et al., 2016), and this has been shown to 

correlate with dispersal distance and hence range size (Sonkoly et al., 2017). Therefore, short-

lived plants are expected to have larger range sizes because they have higher reproductive output 

and dispersal potential, but they also have low competitive ability and short generation times, 

which might decrease establishment success and increase genetic isolation and speciation 

respectively, resulting in an overall lower range size (Sheth et al., 2020). 

 

1.1.3 Grass dispersal modes 

The dispersal of plant seeds is likely to influence the range size of certain species because long-

distance dispersal (Thomson et al. 2018) is the major mechanism for range expansion and 

invasion of a species into new suitable environments (Murray et al., 2002; Kristiansen et al., 

2009). Environmental factors such as fire and herbivory are likely to influence grass 

reproduction and also dispersal (Forrestel et al., 2015; Archibald & Hempson, 2016; Linder et 

al., 2018). Grasses are mainly wind pollinated, although bees and other insects feed on grass 

pollen, thereby contributing to the pollination process (Clayton & Renvoize, 1986; Kellogg, 

2015). In wind-pollinated plants, height is important for gene-flow (Gallagher, 2016; Boucher et 

al., 2017), and in plants with larger inflorescences outcrossing is likely to appear frequently 

because large inflorescences produce many seeds (Kellogg, 2015). Grass species are shown to 

vary morphologically between clades and due to that, certain dispersal syndromes of floral traits 

would likely be associated with particular strategies for dispersal (Kellogg, 2015). 

 



22 
 

Epizoochory and endozoochory are dispersal modes that may play an important role in the 

evolution and life history of grass species (Rosas et al., 2008). Both epizoochory and 

endozoochory can be effective mechanisms for dispersing seeds over long distances (Rosas et 

al., 2008; Anderson et al., 2014). More studies are still needed on why endozoochory species 

become dominant in certain environments where there is a high population of herbivores 

(Anderson et al., 2014). Based on the literature one would expect that animal-dispersed seeds 

would have larger range sizes than wind-dispersed seeds (Rosas et al., 2008; Anderson et al., 

2014), and that the importance of grass height in driving dispersal distance (and therefore, 

potentially range size) would be higher for wind-dispersed seeds (Thomson et al., 2018). The 

positive relationship between seed mass and dispersal structure mass is thought to be useful to 

help larger seeds to disperse further (Edwards et al., 2006). 

 

1.2 Rationale 

The first comprehensive account of the geographical distribution and plant characters of the ± 

978 southern African grass species in ± 200 genera was by Fish et al. (2015). This, together with 

geographic location data from GBIF, provided an opportunity to study the drivers of range size 

and dispersal of the southern African native grass species in sub-Saharan Africa, and to test 

theories around the relative importance of dispersal potential, niche breadth, environmental 

variability and age as drivers of range size (Sheth et al., 2020). Grass floral structures vary 

greatly but we have very little understanding of their functional significance. Therefore it was 

first necessary to determine what floral structures and syndromes exist in African grass species, 

how these are correlated with key drivers of grasslands such as fire and grazing, and which 

dispersal syndromes these floral structures are associated with. Quantifying this floral trait 

diversity and its ecological correlated will enable better understanding of how floral traits link 

with specific dispersal syndromes in this important plant family, and importantly, the degree to 

which they are associated with other key plant characters and the broader life history strategy 

schemes shown in tropical grasslands.  

 

 

 

 



23 
 

1.3 Aims and objectives 

The study aims to understand the drivers of range size and dispersal traits of grasses in Africa 

with the purpose of quantify differences between clades and functional types, and to determine 

the floral traits that likely influence dispersal modes.  

 

The thesis is written as three separate data chapters, each intended to be submitted as a stand-

alone manuscript. Chapter 2 has already been published in the Journal of Biogeography. In this 

chapter I aimed to understand the geographical distribution of grasses in sub-Saharan Africa with 

reference to key plant traits thought to affect range size in this family (Poaceae). Specifically, to 

test hypotheses on the importance of plant height and lifespan in determining range size and 

invasion potential in the context of their evolutionary history. The objectives are: to quantify the 

range size of the full data set of 757 native grass species in 144 genera and 12 tribes to southern 

Africa and were estimated for the sub-Saharan African region and I analysed the range size as a 

predictor of invasiveness of the 250 grass species that are native to South Africa and that have 

been introduced to Australia, Chile, Europe and/or the USA. 

Chapter 3 has been written to be submitted to the Journal Biotropica. In this chapter I aimed to 

describe the range of floral structures in a range of tropical grasses from African countries and 

assess how they covary and whether one can identify particular floral trait syndromes. I 

quantified floral traits of nearly 200 Poaceae species from savanna and grassland ecosystems in 

southern Africa and explored how their floral structures co-vary and correlate with other 

functional characteristics such as grass height. Using field information on the dominance 

disturbance regime of 163 of these grass species I tested whether certain floral traits are more 

associated with fire vs grazing. 

Chapter 4 has been written to be submitted to the Journal of Vegetation Science: Here I 

expanded my analysis to a global scale, but focused on just one grass clade which varied in its 

floral structures. The aim was to assess how dispersal syndrome (inferred from floral structures 

and other functional traits) and evolutionary history affect range size in the grass subtribe 

Eleusininae – a tropical grass clade with variation in floral structures. i.e. I integrated 

information from both Chapters 2 and Chapters 3 to test some of the hypotheses that arose 

from that work. I systematically sampled 97 grass species from 29 genera of the subtribe 



24 
 

Eleusininae across the globe. The objectives were to quantify key dispersal traits, age, and range 

size and test the relationship between range size and interaction between plant height and lemma 

awn state (absent/present), caryopsis and genus age. 

  



25 
 

Chapter 2 | Plant height and lifespan predict range 

size in southern African grasses 

 

This chapter has been published in the Journal of Biogeography 

 
Mashau, A. C., Hempson, G. P., Lehmann, C. E. R., Vorontsova, M. S, Visser, V. & Archibald, 

S. (2021). Plant height and lifespan predict range size in southern African grasses. Journal of 

Biogeography. 48(12): 3047–3059. https://doi.org/10.1111/jbi.14261 

 

AUTHORS’ CONTRIBUTIONS 
 

S.A, C.E.R.L., G.P.H and M.S.V. conceived the idea; A.C.M and V.V. collected the data; 

A.C.M, G.P.H. and S.A. analysed the data; V.V. advised on the analyses; A.C.M., S.A. and 

C.E.R.L. led the writing; G.P.H. prepared the figures, and all authors provided comments and 

feedback on drafts of the manuscript. 

  



26 
 

2.1 | Abstract 

Aim To understand the geographical distribution of grasses in sub-Saharan Africa with reference 

to key plant traits thought to affect range size in this family (Poaceae). Specifically, to test 

hypotheses on the importance of plant height and lifespan in determining range size and invasion 

potential in the context of their evolutionary history.  

 

Location Sub-Saharan Africa. 

 

Taxon Poaceae 

 

Methods The range sizes of 757 grass species native to southern Africa were estimated for the 

sub-Saharan African region from geo-referenced herbarium records using the alpha hull function. 

Phylogenetic generalised least squares models and linear mixed effects models were fitted to test 

whether grass range size was related to plant height and lifespan. Tribe-level relationships 

between range size and plant height were assessed with linear models. For species introduced to 

other continents, generalised linear mixed effects models were fitted to test whether invasiveness 

was related to native range size, plant height and lifespan. Differences in native range size 

among species in four invasion-related categories were assessed with linear mixed effects 

models. 

 

Results Grass range sizes are larger for taller species and for species with shorter lifespans. The 

relationship between plant height and range size varies widely among tribes, with some range-

restricted tribes having a non-significant effect on plant height. Grasses with larger native range 

sizes and shorter lifespans are more likely to become invasive after being introduced to other 

continents. Grass species introduced to other continents have larger native range sizes than those 

that have not, and native range size increases along the introduced-naturalised-invasive 

continuum. 

 

Main conclusions The increased dispersal opportunities of annual-biannual grasses appears to 

have a greater positive effect on range size than do the longer generation times of perennial 

grasses. Grass height has and continues to be an important driver of grass biogeography, with 



27 
 

implications for understanding the spread of certain grass tribes over the Miocene. Factors that 

promote large native range sizes are also likely to increase the probability of a species becoming 

invasive. 

 

Keywords: alpha hull, biogeography, distribution, extent of occurrence (EOO), invasive, 

phylogeny, Poaceae, range size  



28 
 

2.2 | Introduction 

The geographical area a species occupies is a complex product of environmental, competitive, 

geographic and biological factors (Brown et al., 1996; Gaston, 2003; Morueta-Holme et al., 

2013; Sheth et al., 2020). Within even a single genus, species can vary in their range size from 

narrow endemics to almost cosmopolitan distributions (Fish et al., 2015). Exploring the 

determinants and ecological consequences of variation in range size has been the subject of 

research for decades (Brown et al., 1996) to gain insight into the evolutionary origins and 

ecological characters of species and has also been used to explain species richness (Dexter & 

Chave, 2016). Moreover, human activities impact all parts of the Earth, and range size is 

important for assessing extinction risk and adaptation capacity (Manne et al., 1999; Staude et al., 

2020) and, conversely, the potential for species to become naturalised and invasive when 

introduced to new areas (Pyšek et al., 2009; Hui et al., 2011; Procheş et al., 2012).  

 

In plants, range size is the outcome of multiple underlying factors including intrinsic ecological 

limits such as propagule dispersal potential and propagule establishment success, and relatedly, 

the degree of genetic isolation of different populations (Estrada et al., 2015; Sonkoly et al., 

2017). While the ability to disperse over long distances is one mechanism that can generate large 

range sizes, species with wide distributions may also have broader niche breadths, allowing them 

to be competitive across a diverse range of habitats and environments (Slatyer et al., 2013). 

Moreover large range sizes can also be a consequence of low speciation rates (Gaston, 1998). 

Each of these processes such as dispersal potential, establishment success, and speciation rates 

are the result of multiple organismal traits, with range size an emergent property of these 

interacting processes (Figure 2.1). Interestingly, many of the characters used to explain species 

range sizes are often explored as explanations for invasive species success (Blackburn et al., 

2011), as species invasions necessitate an increase in the organisms’ existing range size. Studies 

have indicated that, once introduced, factors shaping plant reproduction and dispersal 

characteristics are likely as important as habitat suitability and establishment success in 

determining whether a species will become invasive (Pyšek et al., 2009). Supporting these ideas, 

Hui et al. (2011) demonstrated that invasive Acacias are more likely to have larger native range 

sizes in Australia than non-invasive species. 



29 
 

 

Figure 2.1 Conceptual diagram showing the various mechanisms by which grass height and 

lifespan could affect range size. Solid lines represent positive relationships and dashed lines 

represent negative relationships. Plant height can increase range size by increasing dispersal 

potential, but decrease it through reduced relative reproductive output and thus reduced dispersal 

opportunities. Likewise, plant height increases competitive ability, which increases establishment 

success and can lead to larger range sizes, but long generation times and slow mutation rates will 

increase genetic isolation and promote speciation, which results in smaller range sizes. 

Moreover, short-lived plants are expected to have larger range sizes because they have higher 

reproductive output and dispersal potential, but they also have low competitive ability and short 

generation times, which might decrease establishment success and increase genetic isolation and 

speciation respectively, resulting in an overall lower range size. Therefore, the slope of the 

relationship between plant height, lifespan and range size helps to determine which of these 

processes is more important for explaining patterns in the grass family. These are not the only 

traits or mechanisms affecting range size; for a comprehensive discussion, please see Sheth et al. 

(2020).  

 

There is much interest in how habitat suitability determines range size, and this is also important 

for predicting how range sizes will vary into the future as a product of environmental change. 

For example, the frequently observed relationship between latitude and range size (Rapoport’s 

rule; Stevens, 1989) has been explained with reference to the larger seasonal variation 

experienced at higher latitudes that enables organisms to succeed in a wider range of 

environments (Morin & Lechowicz, 2011; Morueta-Holme et al., 2013). Other studies have 

found that biome area, or the extent of suitable habitat, are important determinants of range size 

(Gallagher, 2016; Sheth et al., 2020). However, Baselga et al. (2012) found that while 

environment was particularly important for determining range size in widespread species, 



30 
 

dispersal limitation was a more important control on range size in narrowly distributed species. 

Wind-pollination is also thought to increase plant range sizes, because long-distance pollen 

transport enables new populations on the edge of the species range to remain in genetic contact 

with range centres, while also diminishing dependence on specific animal pollinators (Gallagher, 

2016). Relatedly, self-pollination is a further mechanism shown to promote range size in plants, 

likely due to the higher establishment success in new environments when freed from the 

constraint of mate limitation (Grossenbacher et al., 2015). A recent meta-analysis by Sheth et al. 

(2020) of the factors predicting geographic range size in plants showed niche breadth to be 

consistently important, and although evidence for the role of other proposed drivers such as 

dispersal ability was more varied, concluded that both intrinsic and extrinsic factors will 

inevitably shape the edge of species distribution ranges.  

 

Plant height, through impacting both ecological (Westoby, 1998; Diaz et al., 2016) and 

evolutionary processes (Lanfear et al., 2013; Boucher et al., 2017) is likely key in determining a 

species’ geographic range size. For example, taller plant species have a larger dispersal potential 

(Thomson et al., 2011), and are therefore more likely to expand their range by encountering new 

suitable habitats (e.g. Murray et al. 2002; Kristiansen et al. 2009). Height can also increase 

competitive ability (Falster & Westoby, 2003), and therefore establishment success. From an 

evolutionary perspective height in plants is positively associated with generation times due to 

slower mutation rates and therefore lower rates of speciation that can also facilitate larger range 

sizes (i.e., it is more likely that geographically isolated individuals will remain within the same 

species due to both high dispersal capacity and low mutation rates; Lanfear et al., 2013). 

Conversely, small plants invest proportionally more into reproduction (Niklas, 2004), which may 

increase dispersal potential (Sonkoly et al., 2017), although their smaller seeds tend to have 

lower survival and establishment rates (Moles & Westoby, 2006).  

 

Plant lifespan is likely to independently affect range size through impacts on reproduction and 

establishment (Figure 2.1). Annual plants with their large investment in reproduction (Wilson & 

Thompson, 1989) may increase both the likelihood of dispersal and establishment success and 

thereby act to increase range size (Estrada et al., 2015). However, the short generation times of 

annual plants might increase diversification rates and reduce range size, as has been shown in 



31 
 

some animals (Boucher et al., 2017). Therefore, both lifespan and plant height have the potential 

to influence range size via multiple, sometimes contradictory pathways (Figure 2.1). The most 

important factor, and the mechanism by which it works, is likely to be context-dependent both in 

terms of the ecosystem and the organism (Sheth et al., 2020). 

 

The grass family represents a unique opportunity for exploring the role of plant height and 

lifespan in driving range size. Ecosystems dominated by Poaceae cover approximately 31–43% 

of the land surface globally (Gibson, 2009; Linder et al., 2018; Archibald et al., 2019), and they 

spread to achieve their current dominance from the start of the Miocene, 10–20 million years ago 

(Strömberg, 2011). Grass species range sizes vary from narrow endemics found on just single 

hillsides (e.g. Pentameris trifida (Galley) Galley & H.P. Linder and Trisetopsis barbata (Nees) 

Röser & Wölk) to species with wide pantropical distributions (e.g. in Hyparrhenia hirta (L.) 

Stapf and Themeda triandra Forssk.). Grasses show a wide range of life forms and lifespan 

strategies – plant height ranges from < 10 cm to > 4 m (Clayton et al., 2015; Fish et al., 2015). 

Grasses are largely wind-pollinated but display a bewildering variety of dispersal syndromes 

(Clayton, 1990; Kellogg, 2015). These dispersal syndromes tend to be associated with particular 

grass clades, as the floral attributes of the grasses are strongly linked to their evolutionary history 

and are therefore phylogenetically constrained and are also key in morphological taxonomy 

(Doust et al., 2014; Kellogg, 2015). Grasses show both C3 and C4 photosynthetic pathways that 

are also phylogenetically constrained: different grass clades dominate in different environmental 

conditions (Edwards & Smith, 2010; Visser et al., 2012), and evolved at different times (Hackel 

et al., 2018). Therefore, understanding relationships between plant height, lifespan and range 

size within and among grass clades could help assess the relative importance of these factors in 

understanding the distribution of grasses globally. Finally, grasses are some of the most 

consequential invaders globally and understanding how functional traits constrain range size in 

this family could help predict invasiveness (Hui et al., 2011; Canavan et al., 2019). Tall annual 

grasses have high probabilities of establishment outside their native ranges and tend to be 

naturalised in warm climates (Monnet et al., 2020). However, it has not been determined whether 

height and lifespan are associated with larger native range sizes.  

 



32 
 

We quantified range size in 757 grass species indigenous to southern Africa, representing 12 

tribes and 144 genera. We aimed to assess the importance of height and lifespan in determining 

range size and whether these characters help to explain the likelihood of grass species becoming 

invasive. We focus on plant height and lifespan as characters readily available for all 757 species 

as determinants of range size. In Figure 2.1, we highlight how plant height and lifespan have the 

potential to influence range size via multiple mechanisms. Moreover, it should be possible to 

elaborate on other range size constraints within grasses by comparing these relationships among 

tribes. For example, the area suitable for C3 grass photosynthesis in sub-Saharan Africa is limited 

to montane and winter rainfall regions, principally the southernmost part of the continent (Vogel 

et al., 1978; Scott, 2002). Habitat suitability would therefore be expected to be the major 

constraint on the range size of C3 grasses, and in most C3 grass tribes the relationship with height 

or lifespan would then be less apparent than in tribes primarily comprised of C4 species. 

Likewise, if strong relationships were found between plant height and range size in tribes with 

particular floral structures and dispersal syndromes, this would be evidence that the effect of 

height on dispersal is the dominant mechanism driving this relationship (rather than generation 

time). Overall, we expected a general positive relationship between range size and plant height 

across the region. With respect to lifespan, it is unclear whether annual-biannual or perennial 

grasses should a priori be expected to have larger range sizes: 1) perennial grasses have longer 

generation times that should reduce speciation rates and thus promote range sizes, while 2) 

annual-biannual grasses produce more seeds that are also smaller which would likely enhance 

dispersal opportunities and distances, and hence their range sizes. We expected that species that 

have been introduced to other continents are likely to have larger native range sizes than non-

introduced species, because widespread species are more likely to be encountered and 

intentionally or accidentally introduced to new areas. Following introduction, we expect that 

factors that promote larger native range sizes will likely also enhance the probability of a species 

becoming invasive.  

 

 

 

 

 



33 
 

2.3 | Materials and Methods 

2.3.1 Species occurrence data and mapping 

We limited our study to native species occurring in five southern African countries (Namibia, 

Botswana, Lesotho, Eswatini and South Africa), to make use of the unique and well-curated 

species occurrence and trait dataset prepared by Fish et al. (2015). We extracted and analysed all 

occurrence records of native southern African Poaceae from herbarium specimens housed in the 

National Herbarium (PRE), Pretoria; Compton Herbarium (NBG and SAM), Cape Town; 

KwaZulu-Natal Herbarium (NH), Durban; herbarium acronyms following Index Herbariorum 

(Thiers, 2020). All the above-mentioned herbaria are managed by the South African National 

Biodiversity Institute (SANBI), held in the Botanical Database of Southern Africa (BODATSA, 

2019), including the species identifications recently confirmed in preparation of Fish et al. 

(2015). However, the range sizes of these southern African species were then calculated across 

the whole sub-Saharan African region, making use of a total of 138 953 locality records, to get a 

realistic indication of the ranges of widespread species. Species occurrences outside Africa were 

not included in this study. 

 

To improve range size estimations for the whole of sub-Saharan Africa, the geo-referenced data 

from BODATSA/BRAHMS database were augmented with location data from the Global 

Biodiversity Information Facility (GBIF.org, 2019). The occurrence data for indigenous species 

identified to species-level were extracted from BODATSA and GBIF. The “CoordinateCleaner” 

package (Zizka et al., 2019) was used to clean the occurrence data by removing all records with 

the following issues: no geographical coordinates, duplicates, localities in the sea or other 

waterbodies, country centroids and localities of biodiversity institutions. Intraspecific taxa 

including varieties and subspecies were merged to species-level. The distribution map of species 

occurrences in our study (Figure 2.2) represents sampling intensity (records) prepared using R (R 

Development Core Team, 2021). The occurrence data for Africa are too sparse to be confident 

about quantifying the environmental requirements (or niche breath) of all species in this analysis. 

Therefore, we were unable to explicitly test the role of niche breath in controlling range size (but 

see discussion below).  



34 
 

 

Figure 2.2 Map of the study area showing the number of GBIF records for Poaceae per quarter 

degree grid square, which provides an indication of the variation in sampling effort across the 

continent. The 757 species assessed in this study are all native to the region occupied by the five 

southern African countries outlined in black, however, their range sizes were calculated for the 

entire sub-Saharan Africa region including Madagascar. 

 

2.3.2 Species trait data 

Maximum average plant height in millimetres was obtained from herbarium specimens collected 

in southern Africa, by measuring from the base of the culm to the tip of inflorescence during data 

collection towards Fish et al. (2015). Lifespan is the length of the living cycle of a plant, and all 

species were scored as either annual-biannual (i.e. annual or biannual) or perennial following 

Fish et al. (2015). Photosynthetic type (i.e. C3 or C4), was obtained for each grass species from 

Osborne et al. (2014). As photosynthetic type is strongly linked with evolutionary history in 

grasses, we did not include it in our analyses, but we did use it to help interpret the results.  

 

2.3.3 Range size calculations 

Methods used to calculate range size vary from underestimates, such as area of occupancy 

(AOO; only grid cells where the species was physically observed), to overestimates, such as 



35 
 

estimating the extent of occurrence (EOO) by fitting a convex hull that encompasses all recorded 

occurrence data points (Gaston & Fuller, 2009). Burgman & Fox (2003) propose that it is more 

appropriate to use an alpha hull method (Edelsbrunner et al., 1983), as this avoids some of the 

more egregious overestimates of the convex hull method, but still makes some assumptions 

about presence between scattered occurrence records. The alpha hull method removes all edges 

from the convex hull that exceed the value of the mean edge length (L) multiplied by alpha (α; 

i.e. Li > L x α). Thereafter, the total area of all remaining triangles is taken to be the range size 

(Burgman & Fox, 2003). As the value of alpha increases, it eventually causes the alpha hull to 

become equivalent to the convex hull, while small alpha values make the alpha hull become 

scattered points (Burgman & Fox, 2003; Hui et al., 2011).  

 

We estimated range size using the “EOO.computing” function (extent of occurrence) in a 

development version of the ConR package kindly provided by Gilles Dauby (Dauby et al., 2017; 

Dauby, 2020). This version incorporates a planar mode that allows range size to be estimated 

using the alpha hull method and projected coordinates, thus partially accounting for the effect of 

Earth’s curvature on range size estimates; we used the Africa Albers Equal Area Conic 

projection for our range size estimates. We visually assessed the estimated distribution ranges for 

well-known species produced by the use of different alpha values (see Appendix A: Figure S2.1 

for examples), with expert opinion (A. C. Mashau) recommending the selection of alpha = 

200 km (with 10 km buffer) for our analyses. This choice was felt to provide an appropriate 

compromise between overestimating ranges in well sampled regions, and underestimating ranges 

in poorly sampled regions (Appendix A: Figure S2.1). We found that using alpha = 100 km 

(5 km buffer), 200 km or 300 km (15 km buffer) did not change the overall results and 

conclusions of the analyses described below, because although estimated range sizes are highly 

sensitive to alpha values, the relative differences in range size between species remain 

approximately the same, and produce the same relationships with height and lifespan (see 

Appendix A: Tables S2.1-S2.4 and S2.6-S2.8). Alpha hulls cannot be computed for species with 

fewer than three occurrence records. In these cases, we used the “AOO.computing” function 

(area of occurrence) with raster grid sizes of 10 km, 20 km and 30 km to provide range size 

estimates to complete the data sets with alpha values of 100 km, 200 km and 300 km 

respectively. We used 20 random raster grid starting positions; the analysis determines how 



36 
 

many raster grid cells the species records are likely to occupy, and then sums the area of these 

grid cells.  

 

2.3.4 Grass phylogeny 

The checklist of southern African native grass species in Fish et al. (2015) was used to select the 

relevant branches from the grass phylogenetic tree by Spriggs et al. (2014) and match them. The 

keep. tip function from the R package “ape” (Paradis et al., 2004) was used to keep only the 

genus-level branch tips. This resulted in a genus-level phylogenetic tree which contained 120 of 

the 144 genera, covering 350 of the 757 native grass species from southern Africa in the dataset 

(Appendix A: Figure S2.2).  

 

2.3.5 Statistical analyses 

2.3.5.1 Phylogenetically controlled analysis of range size 

Phylogenetic generalised least squares (PGLS; pgls function in “caper” R package; Orme et al., 

2018) models were fitted to test whether species range size was influenced by plant height and 

lifespan. The analysis was restricted to the 350 species included in the grass phylogeny estimated 

by Spriggs et al. (2014), which was used to account for potential non-independence among 

species arising from relatedness. Branch lengths were optimised for the full additive model via 

maximum likelihood estimation of Pagel’s lambda (), with this  estimate subsequently used in 

all candidate models (Pagel 1997, 1999; Orme et al., 2018). Range size (km2) was log-

transformed prior to analyses, with the full set of candidate models comprising height (mm; log-

transformed) and lifespan (two-level factor: “annual-biannual” or “perennial”) as predictors 

fitted independently, additively and as an interaction. In this and all subsequent analyses, model 

selection was performed based on Akaike’s Information Criterion (AIC), with the simplest 

model with ΔAIC < 4 relative to the lowest model AIC value adopted as the best model 

(Burnham et al., 2011). 

 

2.3.5.2 Range size analysis for the full species dataset 

Linear mixed effect models (LMMs) were fitted to test the relationship between range size and 

plant height and lifespan, which were fitted as fixed effects. The analysis included all tribes with 



37 
 

more than five species, resulting in a dataset of 757 species in 144 genera and 12 tribes. The 

model selection was performed based on Akaike’s Information Criterion (AIC), with the 

simplest model with ΔAIC < 4 relative to the lowest model AIC value adopted as the best model 

(Burnham et al., 2011). The random effects component of the models accounted for differences 

in intercepts among grass genera nested within tribe. Range size (km2) was log-transformed to 

conform to a normal distribution prior to analyses, with the full set of candidate models 

comprising height (mm; log-transformed) and lifespan (two-level factor: “annual-biannual” or 

“perennial”) as predictors fitted independently, additively and as an interaction. Maximum 

likelihood and t-tests using Satterthwaite’s method (lmerModLmerTest; Kuznetsova et al., 2017) 

were used to fit and calculate approximate p-values for these models.  

 

2.3.5.3 Tribe level range size vs plant height relationships 

Linear regression models were fitted to assess the relationship between range size and plant 

height and plant lifespan for each of the 12 tribes. Range size (km2) and height (mm) were both 

log-transformed prior to fitting the models. Lifespan was omitted from models for Arundineae, 

Oryzeae and Tristachydeae due low representation of annual species (<= 2 species). 

 

2.3.5.4 Range size as a predictor of invasiveness 

The degree of invasiveness of 250 grass species that are native to South Africa and that have 

been introduced to Australia, Chile, Europe and/or the USA was assessed. Due to the lack of data 

on invasive status for most countries and the difficulty in acquiring these, we used the 

determinations for the four regions selected by Visser et al. (2016). Species were classified into 

three categories following Visser et al. (2016), based on how far along the “introduction-

naturalisation-invasion” (INI) continuum they had progressed (Blackburn et al., 2011): 1) 

introduced (but not [yet] naturalised or invasive), 2) naturalised (i.e. introduced and now 

naturalised but not [yet] invasive), and 3) invasive (i.e. introduced, naturalised and now 

invasive). Generalised linear mixed effect models (GLMMs) were fitted to test if native range 

size (i.e. in sub-Saharan Africa), plant height or lifespan predict whether species have become 

invasive or not when introduced to other continents. Binomial models with a logit link function 

were fitted with species classified as invasive scored as 1, and introduced or naturalised scored as 



38 
 

0. Range size (km2) and height (mm) were both log-transformed prior to analyses. Tribe was 

fitted as a random effect, with genus omitted due to model convergence issues arising from the 

particular subset of introduced species. Candidate models included the full set of combinations of 

these variables. In a separate analysis, a LMM was fitted to test for differences in range size (the 

response) among each of the three INI invasion categories, with the addition of another category 

for those species that were not introduced to other continents (the only fixed effect). Genus 

nested within tribe was fitted as a random effect. The model selection was performed based on 

Akaike’s Information Criterion (AIC), with the simplest model with ΔAIC < 4 relative to the 

lowest model AIC value adopted as the best model (Burnham et al., 2011). All analyses were 

done in the R environment (R version 3.5.1; R Development Core Team, 2021). 

 

2.4 | Results 

The median range size of southern African Poaceae was c. 120 000 km2, with an interquartile 

range of c. 25 000 km2 to 520 000 km2 (Figure 2.3). However, 7 grass species have range sizes > 

5 million km2 – i.e. they cover over half of the total area of sub-Saharan Africa (land area c. 9 

200 000 km2).  

 

Figure 2.3 Histogram of the range sizes (km2, log-scale) of southern African grasses, estimated 

using the alpha hull method with alpha = 200 km. Tribe-level range size distributions are 

indicated by stacked colour bands. 

 

 

 



39 
 

2.4.1 Phylogenetically controlled analysis of range size 

Grass species range sizes were strongly related to both plant height and lifespan. The best PGLS 

model included height and lifespan as additive effects (Appendix A: Table S2.1 & S2.2; Figure 

S2.3; r2 = 0.14), with no clear evidence for an interaction between these predictors (p = 0. 828; 

ΔAIC = 1.952). Plant height had a positive effect on range size (β ± SE = 0.876 ± 0.154, p < 

0.001), and perennial grasses had significantly smaller range sizes than annual-biannual grasses 

(β ± SE = -1.098 ± 0.185, p < 0.001). When range size and height are back-transformed to their 

original measurement scales, the model suggests that the range size of an annual-biannual grass 

will increase over the interquartile range of observed grass heights (550 to 1200 mm) from c. 

230 000 km2 to 455 000 km2, and for a perennial grass from c. 77 000 km2 to 152 000 km2. The 

 estimate of 0.681 suggests that the range size of grasses is structured to some extent by 

phylogenetic relationships and grass evolutionary history. 

 

2.4.2 Range size analysis for the full species dataset 

The LMMs fitted to data for all southern African grass species confirmed that range size was 

significantly related to both plant height and lifespan (Figure 2.4). The best model included 

height and lifespan as additive effects (Appendix A: Table S2.3 & S2.4; Figure S2.4; marginal r2 

= 0.08, conditional r2 = 0.25), with no clear evidence for an interaction between these predictors 

(p = 0.662; ΔAIC = 1.808). Consistent with the phylogenetic analyses, height had a positive 

effect on range size (β ± SE = 0.872 ± 0.127, p < 0.001), and range sizes for perennial grasses 

were significantly smaller than for annual-biannual grasses (β ± SE = -0.870 ± 0.170, p < 0.001). 

Examination of the tribe-level intercept in the random effects suggests that there are unaccounted 

for effects that result in both the Danthonieae and Poeae having smaller range sizes than the 

other tribes and the Andropogoneae having unexpectedly large ranges (Appendix A: Figure 

S2.5).  



40 
 

 

Figure 2.4 Relationships between range size (km2, log-scale) and plant height (mm, log-scale) 

for 757 southern African grasses with annual-biannual (open symbols and dashed line) or 

perennial (solid symbols and line) lifespans, as estimated by a linear mixed effects model. Genus 

nested within tribe was fitted as a random intercept term in the model to partially account for 

evolutionary constraints. 

 

2.4.3 Tribe level range size vs plant height relationships 

The linear models showed that most C4-dominated tribes (Andropogoneae, Aristideae, 

Eragrostideae, Paniceae and Zoysieae) had positive significant relationships with plant height 

(Figure 2.5; Appendix A: Table S2.5), with the exceptions being the Cynodonteae and 

Tristachydeae, where height had a non-significant effect on range size. Among the C3 tribes, the 

Arundineae, Oryzeae and Poeae had significant and positive height vs. range size relationships, 

but this relationship was non-significant for the Danthonieae and Ehrharteae.  



41 
 

 
Figure 2.5 Tribe-level relationships between range size (km2, log-scale) and plant height (mm, 

log-scale) and plant lifespan (annual-biannual vs. perennial) for 757 species in 144 genera and 12 

tribes of southern African grasses. Linear models were fitted to species range size data for each 

tribe separately, with height fitted as a predictor in all models, and lifespan fitted where annual-

biannual and perennial categories were represented by five or more species each. Solid lines 

represent a significant effect of plant height, and dashed lines represent a non-significant effect 

of plant height; shaded areas represent the 95% confidence interval for height parameter 

estimates. Red lines and shading represent annual-biannual species, blue represents perennial 

species, and black lines with grey shading represent all lifespans. The significance of lifespan 

effects on range sizes are indicated in each panel (“A-B vs. P” = annual-biannual vs. perennial), 

where *** = p < 0.001, * = p < 0.05 and NS = p > 0.05. The photosynthetic pathways (i.e. C3 

and/or C4) occurring in each tribe is shown in brackets after the tribe name. 

 

2.4.4 Range size as a predictor of invasiveness 

The invasiveness data revealed that the probability of a South African grass becoming invasive 

after being introduced to other continents was related to both its native range size and lifespan 

(Figure 2.6). The best GLMM model included range size and lifespan as additive effects, and 

tribe as a random effect (Appendix A: Table S2.6 & S2.7; marginal r2 = 0.12, conditional r2 = 



42 
 

0.14). Invasiveness was positively related to range size (β ± SE = 0.576 ± 0.167, p < 0.001), and 

perennial grasses had marginally significant lower probability of becoming invasive than annual-

biannual grasses (β ± SE = -0.670 ± 0.349, p = 0.055).  

 

Figure 2.6 Probability of South African grasses becoming invasive following introduction to 

other continents as a function of their native range size in sub-Saharan Africa (km2, log-scale) 

and lifespan (annual-biannual: open symbols and dashed line, or perennial: solid symbols and 

line). Probabilities were estimated by fitting a binomial generalised linear mixed effects model 

fitted to data for 250 grasses categorised as invasive (1) or introduced or naturalised (0) 

following Visser et al. (2016). Tribe was fitted as a random intercept in the model. 

 

The LMM using all grass species confirmed that range size differences existed between invasion 

categories (Appendix A: Table S2.8; Figure 2.7 & S2.6). Species that had not been introduced to 

other continents had significantly smaller range sizes than all other categories (54 567 km2; p < 

0.001). Native range size increased steadily along the INI continuum: introduced (377 566 km2), 

naturalised (496 481 km2) and invasive (1 026 022 km2), although the difference in range size 

between introduced and naturalised species was not significant (p > 0.05). 



43 
 

 

Figure 2.7 Boxplot showing variation in native range sizes among 757 southern African grasses 

after classification into four invasion status categories: 1) not introduced to other continents, 2) 

introduced (but not [yet] naturalised or invasive), 3) naturalised (i.e. introduced and now 

naturalised but not [yet] invasive), and 4) invasive (i.e. introduced, naturalised and now 

invasive). Differences in range size among invasion categories were assessed using a linear 

mixed effects model, with genus nested within tribe fitted as a random effect. Categories with 

different letters are significantly different (p < 0.05). 

  



44 
 

2.5 | Discussion 

We found that grass height has a positive correlation with range size, where taller grasses have 

larger range sizes (Figure 2.4). The strength of the plant height-range size relationship, which 

persists when controlling for phylogeny, was expected based on well-documented relationships 

between plant height and increased dispersal ability (Thomson et al., 2011) and decreased 

diversification (Boucher et al., 2017), and mutation rates (Lanfear et al., 2013). However, there 

is also potentially an ecological factor related to competitive abilities: tall grasses tend to 

outcompete small grasses and remain dominant in an occupied area (Falster & Westoby, 2003).  

 

Range sizes of annual-biannual grasses were larger than for perennial grasses in sub-Saharan 

Africa (Figure 2.4). There are several reasons why within the grass family, annual-biannual 

grasses might be expected to have larger range sizes. One reason may be because annual-

biannual grass species have higher reproductive allocation than perennial grasses (Wilson & 

Thompson, 1989; Vico et al., 2016), and often also smaller seeds (Moles et a1., 2004), and this 

has been shown to correlate with dispersal distance and hence range size (Sonkoly et al., 2017). 

Perennial grasses such as Hyperthelia dissoluta (Nees ex Steud.) Clayton allocate resources to 

above-ground biomass, clonal reproduction, and rapid height gain (Taylor et al., 2010; Ripley et 

al., 2015) at the expense of reproductive effort. Finally, while annual grasses always flower 

within the first year, many perennial tropical grasses can also produce seed within months of 

germinating (unpublished data S. Archibald and C. Lehmann). Therefore, although annual 

species have short generation times, they are not necessarily always shorter than those of co-

occurring perennial grasses. Overall, our results show that grasses with shorter lifespans have 

larger range sizes, suggesting that, for annual-biannual grasses, the positive effect on range size 

of increased dispersal opportunities and dispersal distance is greater than the negative effect of 

short generation times and hence faster speciation rates (Boucher et al., 2017). 

 

Contrary to our expectations, the strongest positive relationships with height were found in three 

C3 tribes, Oryzeae, Arundineae and Poeae (although note that the Oryzeae showed little variation 

in range size), however, for the C3 Danthonieae and Ehrharteae, the relationship was not 

significant. The C4 clades generally had strong positive relationships with plant height, but the 

Cynodonteae is an exception. These results can in part be explained with reference to habitat 



45 
 

suitability and dispersal syndromes. In particular, Oryzeae and Arundineae are largely wetland 

species (Fish et al., 2015), and by promoting the ability to disperse easily from one isolated 

wetland fragment to another height should strongly drive their range size. Likewise, cool 

environments are found scattered throughout the high-altitude mountains of Africa (Meadows & 

Linder, 1993), and it would be expected that grass species from the Poeae tribe, which includes 

Afromontane specialists, such as Festuca L. and Trisetopsis Röser & Wölk (South African 

species previous classified under Helictotrichon Besser ex Schult. & Schult. f.) would show a 

significant relationship with grass height. In contrast, the C3 tribe Danthonieae is predominantly 

limited to cooler environments in the southern Cape in Africa (Humphreys & Linder, 2013), so 

height (and dispersal ability) should not affect their ranges which are constrained by habitat 

availability (Gallagher, 2016). Linder et al. (2018) argue that frost tolerance allowed subfamilies 

Pooideae and Danthonioideae to invade vast areas during glacial periods. However, the Pooideae 

evolved earlier than the Danthonioideae and this, together with the truncated cold environments 

available in the Southern Hemisphere, has probably prevented the Danthonioideae from 

expanding their ranges as much as Pooideae (Humphreys & Linder, 2013).  

 

Tribe Paniceae is very large, and includes both C3 and C4 species and a wide variety of dispersal 

syndromes. It is not surprising therefore that the relationship with height is less apparent in this 

clade. Likewise, tribe Cynodonteae also contains species with dispersal syndromes ranging from 

the epizoochoric Tragus berteronianus Schult. to endozoochoric Cynodon dactylon (L.) Pers., 

and includes species like Dactyloctenium giganteum Fisher & Schweick. which is thought to be 

dispersed on the feet of waterbirds (personal communication I. P. J. Smit). Although the response 

of dispersal distance to plant height is very well documented for wind-dispersed species 

(Thomson et al., 2011), it is less clear how height might facilitate dispersal with endozoochory – 

in fact, it is possible that there is a negative relationship here, as smaller plants are more likely to 

have their seeds ingested by grazing animals (Anderson et al., 2014). Perhaps as a result, 

Cynodonteae species are generally shorter than other clades as can be seen in Figure 2.5. Clearly 

further research linking dispersal syndromes to height and range size is urgently needed. We do 

not yet have clarity on which propagule traits are associated with endozoochory, epizoochory, 

and wind dispersal in grasses, but from data presented here it seems this might be key to 

explaining biogeographic patterns in this plant family.  



46 
 

 

The tribes Danthonieae and Poeae had smaller range sizes than the other tribes once grass height 

and lifespan had been accounted for, while the Andropogoneae had unexpectedly large range 

sizes (Appendix A: Figure S2.5). Visser et al. (2012) argued that Andropogoneae are uniquely 

adapted to fire, and Schmidt et al. (2011) found species in this clade to be good competitors 

across a wide environmental range. Perhaps these two factors, together with the fact that they are 

generally tall and include multiple annual species (Schmidt et al., 2011; Fish et al., 2015) may 

account for this group’s large range sizes. Interestingly, the Andropogoneae are one of the 

youngest grass clades to have evolved (Welker et al., 2020), and their extremely large ranges 

contradict the age-and-area hypothesis that has been observed in several other plant groups 

(Sheth et al., 2020). Yet again, this highlights the potentially important and under-recognised 

role of dispersal and competition traits in driving range size.  

 

Invasive grasses had larger native range sizes than introduced species (Figure 2.7), and annual-

biannual grasses had a significantly higher probability of being invasive than perennial grasses 

(Figure 2.6). This is the first time this has been demonstrated for the grass family and 

corresponds with findings for Australian Acacia (Hui et al., 2011) and the flora of the Czech 

Republic (Pyšek et al., 2009), where species with large native range sizes are more likely to 

become invasive. The simplest explanation for this is that species with large range sizes are 

likely to be encountered by more people so have increased likelihood and hence frequency of 

being chosen for introduction elsewhere (Duncan et al., 2001). Species with larger native ranges 

may also display greater morphological and genetic variation leading to plasticity and a capacity 

to more rapidly adapt and thrive in novel environment (Buswell et al., 2011). Over the past 

century, African grasses have been sought after for pasture introduction and have been 

extensively introduced around the world (Visser et al., 2016). However, while introduced species 

have larger native range sizes than non-introduced ones, the introduced species that become 

invasive have larger native range sizes still, indicating that some ecological attributes of these 

species promote their invasion success. We found that lifespan, and probably also height, helped 

to explain the relationship between range size and invasiveness. This is not unexpected as 

dispersal is an important factor affecting the propensity of a species to invade (Pyšek et al., 

2009). Although height was not included in the best model, it nonetheless was an important 



47 
 

factor in two of the three models with ΔAIC < 4 (Table S2.6). Canavan et al. (2019) argue that 

tall stature provides numerous ecological advantages to grasses making them much more likely 

to become invasive. Our finding that invasive grasses have large native range sizes could help to 

identify potentially invasive species and manage the risk of introducing them to new 

environments, but it would be worth investigating the mechanisms more closely. 

 

Range size is included in the conservation status of IUCN red listing processes and considered a 

predictor of species extinction risk (IUCN, 2001; Gaston & Fuller, 2009). Grass species with 

small range size include Ehrharta microlaena Nees ex Trin, which is endemic to the Western 

Cape, South Africa. The fact that we have identified some strong life history and architectural 

characteristics that are associated with range size might also be helpful in efforts to further 

identify grass species in need of particular protection, especially those with small range sizes.  

 

2.6 | Conclusion 

Our analyses suggest that plant height has been, and continues to be, an important driver of grass 

biogeography with implications for understanding the spread of certain grass clades both over 

the Miocene and today. Our study has improved our ecological understanding of how grass range 

size varies across sub-Saharan Africa, and challenges the idea that dispersal potential is less 

important than niche breadth or environmental variability as the main driver of range size (Sheth 

et al., 2020). Our results also suggest that in grasses the increased dispersal opportunities and 

distances of annual-biannual grasses have a greater effect on promoting range size in grasses 

than the effect of short generation times on speciation rates. Furthermore, there is also a need to 

understand how floral attributes and dispersal mode relate to range size in grasses, which 

requires further research. Measuring range size helps to understand the evolutionary origins and 

ecological characteristics of a species, and is important for assessing invasion and extinction risk.  

 

  



48 
 

Chapter 3 | Floral trait syndromes in tropical grasses 

and their environmental associations 

 
This chapter has been prepared for submission to the Journal Biotropica 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



49 
 

3.1 | Abstract 

Grass floral structures vary greatly but we have very little understanding of their functional 

significance. Due to the varied dispersal mechanisms shown by grasses, certain syndromes of 

floral traits would likely be associated with particular strategies for dispersal, and consequently, 

different environments. In particular, effective seed maturation and dispersal in fire-prone tall 

grasslands would require different floral trait syndromes than in short, frequently grazed 

ecosystems. Here I quantify floral traits of nearly 200 Poaceae species from savanna and 

grassland ecosystems in southern Africa and explore how their floral structures co-vary and 

correlate with other functional characteristics such as grass height. Using field information on the 

dominance disturbance regime of 163 of these grass species it was tested whether certain floral 

traits are more associated with fire vs grazing and the mean rainfall arranged from 323–1256 

mm.yr-1 in the study areas. Non-metric multi-dimensional scaling (NMDS) was used to illustrate 

how floral traits covaried among grass species, and to group them into syndromes based on these 

traits. Analysis of variance (ANOVA) was used to test whether certain floral trait syndromes 

were more associated with fire vs grazing. I identified four clear floral trait syndromes separated 

largely by awn length and the presence of hooks/prickles or bristles. Long-awned species were 

more likely to be found in frequently burned environments and were also usually taller than 

species without awns. Grazer-dominated systems appear to select for two different floral trait 

syndromes which are no lemma awns, blunt or no callus sharpness. The study has improved our 

ecological and taxonomic understanding of how floral traits differ among the range of tribes in 

one family across African countries. It can help in understanding dispersal limitations in grasses 

and predicting which species are likely to flourish in particular grassland habitats.  

 

Keywords: Floral traits, fire, grazing, lemma awn, spikelet 

 

 

 

 

 



50 
 

3.2 | Introduction 

Grasses (Poaceae) started evolving at least in the late Cretaceous or Paleocene, occurring at or 

after 55–70 million years ago (Christin et al., 2014). The distribution of the grass lineages started 

to spread from their Gondwanan center of origin after the breaking up of the southern 

supercontinent (McLoughlin, 2001; Bremer, 2002; Bremer & Janssen, 2006; Bouchenak-

Khelladi et al., 2010; Christin et al., 2014). Members of the subfamily Pooideae have greatly 

diversified in the northern hemisphere, while the other remaining subfamilies have their greatest 

diversity in the tropics and on the continents that originated from the break-up of Gondwana 

(McLoughlin, 2001; Bremer, 2002; Bremer & Janssen, 2006; Bouchenak-Khelladi et al., 2010; 

Christin et al., 2014; Kellogg, 2015). The grass lineages achieved their world-wide distribution 

due to long-distance dispersal mechanisms (Christin et al., 2014).  

There is a wide diversity of floral structures in grasses, and they are often the main 

morphological characters distinguishing different grass clades (Kellogg, 2000, 2015). The whole 

grass flower is called a spikelet (diaspore) (Kellogg, 2015). The spikelet comprises the axis or 

rachilla with two glumes (bracts) at the base and one or more florets (lemma) borne alternately 

up the rachilla (Fish et al., 2015; Kellogg, 2015). There are fertile and sterile spikelets. Fertile 

grass spikelets function as a female reproductive organ. The grass reproduction occurs inside the 

spikelet. Floral structures are fairly phylogenetically conserved, and there are strong links among 

grass lineages, growth forms and environmental drivers, particularly grazing and fire (Kellogg, 

2000; Kellogg, 2015). Accordingly, it is likely that floral trait syndromes, which are linked to 

both lineages and environmental conditions, will encompass traits that allow effective use of the 

dispersal opportunities in these different environments.  

 

While grass pollination is mostly (but not exclusively) by wind, dispersal agents are more 

diverse and include epizoochory and endozoochory (Soderstrom & Calderón, 1971; Huang et al., 

2002; Sajo et al., 2009; Ruiz-Sanchez et al., 2017). The dispersal of grass seed is closely 

associated with the structure and composition of spikelets (Schrager-Lavelle et al., 2017) (Figure 

3.1).  



51 
 

 

Figure 3.1 Conceptual diagram based on the information from the literature about which floral 

traits are associated with each dispersal syndrome. Also shown are leaf and growth form 

functional traits that would be expected also to be associated with particular dispersal syndromes. 

Plant height and floral traits can function together to influence dispersal mode (either wind, 

epizoochory or endozoochory) and also to change the ecosystem community in a different 

environment.  

 

The major adaptive structures that have facilitated a rich diversity of dispersal modes in grasses 

are the hygroscopic awn – which may or may not be a present, sharp point on the callus, and a 

range of hooks or bristle structures (Peart, 1979; Clayton & Renvoize, 1986; Davidse, 1987; 

Peart & Clifford, 1987; Kellogg, 2015). Rosas et al. (2008) found that the majority of small 

seeds were found undamaged in bison dung and therefore the endozoochory by bison proved to 

be a long-distance dispersal mechanism for small seeds. Others have also found that small, 

smooth, hard seeds or diaspores are associated with endozoochory (Shiponeni & Milton, 2006; 

Rosas et al., 2008) protecting it from the molar mill and during the passage through the gut. 

Moreover, the dispersal unit of endozoochorous plants needs to be sufficiently attractive to 

encourage animals to eat it, so hairs, awns and prickles are likely not to be characteristics of 

endozoochorous grasses. In contrast,  hooks and prickles on the spikelet and lemma awns 

facilitate epizoochoric dispersal (Davidse, 1987; Kellogg, 2015). The lemma awn is a variable 

structure among grasses and has been proposed to affect seed dispersal, as well as germination 

and seedling establishment (Peart, 1979, 1981; Peart & Clifford, 1987; Garnier & Dajoz, 2001; 



52 
 

Elbaum et al., 2007). Grass species with active lemma awns, which produces a twisting motion, 

can help to bury the seeds deeper in the soil and this has been proposed to increase seed survival 

during fires (Roux, 1969; Schrager-Lavelle et al., 2017). Although it has been reported that long 

lemma awns increase short-distance dispersal of about less than 1 m (Diacon-Bolli et al., 2013) 

there are also references indicating that long awns can be an impediment to dispersal by bury 

awns into animal fur (Van der Pijl, 1982; Fischer et al., 1996; Rosas et al., 2008; Clayton et al., 

2015; Fish et al., 2015; Kellogg, 2015; Schrager-Lavelle et al., 2017). The size of the dispersal 

unit can also range widely in grasses – with some species (e.g. Cymbopogon caesius (Hook. & 

Arn.) Stapf, Hyparrhenia hirta (L.) Stapf and Themeda triandra Forssk.) disarticulating their 

entire inflorescence, and others only individual florets. Grass species with large dispersal units 

(inflorescence branch) would enable better wind or water dispersal (Doust et al., 2014). 

However, generally small seeds are also better wind dispersed than large seeds (Thomson et al., 

2011). For more information about the functions of grass flowering structures see Table 3.1 and 

Figure 3.1. 

 

The degree to which plant height affects dispersal depends on the dispersal mechanism 

(Thomson et al., 2011; Mashau et al., 2021). Thomson et al. (2011) documented the response 

between plant height and dispersal distance, but this was more important for wind-dispersed 

seeds and those with adaptations for ectozoochory. Plants dispersed by animals through 

endozoochory are often short, with flowers at the same level as the grass (Janzen, 1984; 

Anderson et al., 2014). Mashau et al. (2021) showed that the range size of some grass clades was 

more strongly related to grass height than others, and hypothesised that this might be related to 

the common dispersal modes in those clades. 

 

The evolution and maintenance of tropical savanna grasslands are associated with fire and 

herbivory, as well as rainfall (Forrestel et al., 2015; Archibald & Hempson, 2016; Linder et al., 

2018). Both fire and herbivore pressures are thought to have increased with the spread of 

grasslands during the Miocene (Forrestel et al., 2015; Archibald & Hempson, 2016; Linder et al., 

2018). In Africa, fire is the dominant consumer in wetter grasslands, and grazing dominates in 

more arid ecosystems (Archibald & Hempson, 2016), but both fire-maintained and grazer-

maintained grassland habitats are common across a wide environmental range and associated 



53 
 

with particular grass species and functional types (Hempson et al., 2015; Solofondranohatra et 

al., 2020). Because fire-prone grasslands are generally associated with lower herbivore numbers 

(Staver & Bond, 2014) and taller grass species (Archibald et al., 2019), one would expect 

dispersal modes would also vary across these grasslands. In particular, traits associated with 

endo- and ectozoochory would be more common under heavy grazing, and traits associated with 

wind dispersal more common in frequently burned grasslands (Anderson et al., 2014). 

Endozoochorous grass species in particular need to attract grazing herbivores (Janzen, 1984; 

Rosas et al., 2008) and require palatable leaves, which promote consumption by herbivores and 

subsequent seed dispersal.  

 

Fire and grazing are environmental factors that are related to abiotic and biotic factors such as 

rainfall and patterns of modern land use (Solofondranohatra et al., 2020). Donaldson et al. 

(2018) showed that when grazing increases in a tall-grass fire-prone ecosystem, the grass species 

are replaced by shorter, more palatable species, but did not investigate how the floral structure 

changed. Solofondranohatra et al. (2020) also found that fire and grazing promote differentiation 

in community composition with divergent growth forms in Madagascar. If these changes also 

result in a turn-over in floral traits and dispersal modes it would have implications for 

biogeographic and evolutionary processes (e.g. population genetics and range size – Boucher et 

al., 2017; Mashau et al., 2021). It would also alter food availability for seed-eating birds and 

rodents (Pakeman, et al., 2002; Cousens, et al., 2010; Godó, 2022). It is well known that f