CLIMATE CHANGE AND SPECIES RANGE SHIFTS

Are there evolutionary consequences of plant–soilfeedbacks along soil gradients?Jennifer A. Schweitzer1*, Ivan Juric1, Tess F. J. van de Voorde2, Keith Clay3,Wim H. van der Putten4,5 and Joseph K. Bailey1

1Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, Tennessee 37996, USA;2Nature Conservation and Plant Ecology, Wageningen University and Research Centres, 6700 AA Wageningen,The Netherlands; 3Department of Biology, Indiana University, Bloomington, Indiana 47405, USA; 4 Department ofTerrestrial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), 6700 AB Wageningen, The Netherlands; and5Laboratory of Nematology, Wageningen University and Research Centre, 6700 ES Wageningen, The Netherlands

Summary

1. Both abiotic and biotic gradients exist in soils, and several of these gradients have been

shown to select for plant traits. Moreover, plants possess a multitude of traits that can lead to

strong niche construction (i.e. plant-induced changes to soils). Our objectives in this paper are

to outline both empirical and theoretical evidence for the evolutionary consequences of plant–soil linkages and feedbacks on plants along soil heterogeneity gradients.

2. We describe a simple mathematical model of plant evolution to explore the relationship

between the sign and magnitude of feedback and the divergence of plant traits. We also

constructed an individual-based simulation model to study the conditions under which

plant–soil feedbacks occur, niche construction evolves, and plant traits diverge.

3. This approach allows us to address specific hypotheses regarding relationships between posi-

tive and negative plant–soil feedback with variation in niche construction, the strength of selec-

tive gradients and the relative importance of local adaptation vs. feedbacks.

4. The models suggest that feedbacks between soils and plants may commonly result in evolu-

tionary interactions. The simulation model indicates that plant traits can diverge with niche

construction and traits can be selected for in response to niche construction. However, the

magnitude of feedbacks and how strongly they evolve depends on the amount of gene flow

and the strength of selective gradients over time.

5. These results suggest that plant–soil feedback can lead to evolution in plants and reveals

new research directions for further inquiry. Questions addressing trade-offs and relationships

between positive and negative feedbacks as well as adaptation and maladaptation of plant

traits represent important frontiers in plant–soil feedback studies.

Key-words: environmental gradients, evolutionary interactions, evolutionary models, genetic

divergence, individual-based models, local adaptation, niche construction, plant traits, plant–soil feedback, plant–soil linkages, selective gradients

Introduction

Soils are one of the first selective environments a seed and

seedling experience, yet relatively little is known about the

evolutionary consequences of plant–soil linkages and their

feedbacks. Elucidating the connections between ecological

interactions and evolutionary processes (known as eco-evo-

lutionary dynamics) is important for understanding how

genetic variation in one species affects community composi-

tion and ecosystem processes and how these may feed back

to shape genetic variation in subsequent generations (see

Table 1 for term definitions); this may be especially perti-

nent to plant–soil feedbacks (PSFs). Feedbacks are funda-

mental to the co-evolutionary process (Thompson 2005),

local adaptation (Clausen, Keck & Hiesey 1940; Johnson

et al. 2010) and the maintenance of biodiversity (Duffy &

Forde 2009; Laine 2009). Plant–soil feedbacks occur when

a change in soil conditions due to the properties/traits of a*Correspondence author. E-mail: Jen.Schweitzer@utk.edu

© 2013 The Authors. Functional Ecology © 2013 British Ecological Society

Functional Ecology 2014, 28, 55–64 doi: 10.1111/1365-2435.12201

plant species affects the fitness of plants of the same species

or other co-occurring species (Kulmatiski et al. 2008; van

der Putten et al. 2013). While there are a wealth of studies

demonstrating evolutionary linkages between plants and

soils with respect to host-specific symbionts and pathogens

(Schmid 1994; Burdon & Thrall 1999; Bever & Simms

2000; Thrall et al. 2006; Lankau 2011), and whole commu-

nities (Schweitzer et al. 2008a; de la Pe~na, Bonte & De

Roissart 2010; Madritch & Lindroth 2011), the evolution-

ary consequences of positive and negative PSFs are largely

unknown for plants. This is due to the relative novelty of

the area of PSF; the term was not coined until the 1990s,

even though the concept has been in practice for much

longer (van der Putten et al. 2013). The connections

between evolutionary processes and PSF are also rarely

explored given the perceived difficulty in disentangling soil

communities and the relationship of soil communities to

soil–nutrient dynamics over temporal and spatial scales

(see Bardgett et al. 2005; Kardol et al. 2013).

Plant–soil feedbacks may be important agents of selec-

tion and drivers of genetic change. Clay & van der Putten

(1999) showed that there is much anecdotal evidence of the

evolution of plant life histories to avoid pathogens and

parasites that drive negative feedbacks. These include

long-distance dispersal (e.g. fleshy fruits, wind-blown

seeds), extended seed dormancy, greater reliance on clonal

growth than seedling establishment and breeding systems

that favour outcrossing for maximizing genetic variation

of offspring (self-incompatibility, dioecy, etc.). Plant spe-

cies (or genotypes) may also be favoured that cultivate a

soil microbial community that acts to suppress pathogen

activity (Kinkel, Bakker & Schlatter 2011) or that maxi-

mises resource uptake. For example, when Andropogon

gerardii ecotypes collected from phosphorus(P)-limited and

nitrogen(N)-limited grasslands were grown with all possi-

ble ‘home’ and ‘away’ combinations of soils and mycorrhi-

zal communities (experimental approach to determine

feedback effects), Johnson et al. (2010) found that soil

fertility was a key driver of local adaptation of the symbio-

ses such that mycorrhizal exchange of the most limiting

soil nutrient resource for each ecotype was maximised.

Moreover, differences in PSF across gradients may lead to

different evolutionary outcomes. For example, a positive

PSF was demonstrated by Pregitzer et al. (2010) across a

gradient of genetic variation, whereby seedlings planted

from 20 randomly collected Populus angustifolia genetic

families into soils conditioned by various Populus species

in the field demonstrated differential survival and perfor-

mance. Even though P. angustifolia soils were less fertile

overall, P. angustifolia seedlings grown in their own soils

were twice as likely to survive, performed better than

P. angustifolia seedlings grown in soils conditioned by

another Populus species or their natural hybrids and

showed a wider range of trait variation. These results show

that positive PSF can have important consequences for

variation in plant phenotypes and indicate the putative

importance of PSF along gradients as a selective agent.

Variation in niche construction by plants, strong envi-

ronmental gradients in soil and a selective response repre-

sent the basic principles of evolution driven by plant–soil

feedbacks. Niche construction occurs when genetically

based variation in plant traits influences the abiotic or

biotic conditions of soil. Feedbacks occur when the fitness

of seedlings vary when grown in soils previously affected

or ‘conditioned’ by plant genotypes or species relative to

soil conditioned by other genotypes or species. Multiple

studies indicate that plants (at the level of phylogenetic

clade, functional group, species or genotype) can affect the

abiotic properties of the soil (i.e. physical and chemical

properties, such as pH) as well as the composition, abun-

dance or activities of the soil community (Hobbie 1992;

Binkley & Giardina 1998; Grayston et al. 1998; Diab el

Arab, Vilich & Sikora 2001; Hamilton & Frank 2001;

Bartelt-Ryser et al. 2005; Madritch, Donaldson & Lind-

roth 2006; Schweitzer et al. 2008b, 2012; Brandt,

Seabloom & Hosseini 2009; Madritch, Greene & Lindroth

Table 1. Definitions of utilized genetic and evolutionary terms

Term Definition

Genetic divergence Accumulation of genetic differences between lineages over time

Genetic variation Variation, within or among species that is explained by underlying genetic factors

Local adaptation Process by which genotypes in a local population have, on average, a higher relative fitness in

their local habitat than genotypes originating from other habitats (may be due to stochastic,

random processes)

Niche construction Process whereby organisms (plants in this case) modify their local environment in some manner

that has both ecological and evolutionary consequences

Maladaptation Deviations from adaptive peaks, whereby fitness is reduced under conditions that are not

perfectly matched to adapted traits and conditions

Plant–soil feedback (PSF) Feedback describes a sequence of interactions in which the result of a process affects the

conditions that initially generate the process. In the context of plant–soil interactions,a change in soil conditions due to properties/traits of the plant (species A), which in turn

affects the fitness of the plant that expressed those traits (species A). This is experimentally tested by

planting seed in ‘home’ soils (those conditioned by the same species/genotype) and ‘away’ soils

(those conditioned by another species/genotype)

Plant–soil linkages Mutual effects of plants on soils (via functional traits) or vice versa. These one-way interactions

do not always lead to feedbacks; however, they are required for feedbacks to occur

© 2013 The Authors. Functional Ecology © 2013 British Ecological Society, Functional Ecology, 28, 55–64

56 J. A. Schweitzer et al.

2009; Bezemer et al. 2010). Studies examining invasion

success, patterns of succession and community biodiversity

have convincingly shown that components of the soil com-

munity commonly mediate feedback responses (Packer &

Clay 2000; Klironomos 2002; Levine et al. 2006; Kardol

et al. 2007; Rout & Callaway 2009; Mangan et al. 2010;

van de Voorde, van der Putten & Bezemer 2012). More-

over, variation in soil biotic communities has been shown

to select for plant traits. For example, Lau & Lennon

(2011) found that simplified soil microbial communities led

to a 50% increase in plant biomass and selection for

reduced specific leaf area and for earlier flowering times in

Brassica rapa, relative to natural microbial communities.

Plant-mediated shifts in soils may also result in specific

feedbacks that have selective outcomes for fitness and

quantitative genetic variation in plants (Bever, Westover &

Antonovics 1997; Burdon & Thrall 1999; Clay & van der

Putten 1999; Gilbert 2002; Pregitzer et al. 2010).

The study of genetic divergence along environmental

gradients is fundamental to understanding adaptive evolu-

tion and diversification and may mediate the evolutionary

outcomes of niche construction. In soils, environmental

gradients such as nutrient availability and pH could repre-

sent strong selective gradients for understanding PSFs in

an evolutionary context. For example, variation in soil

parent materials and underlying chemistry may act directly

as selective agents on plant populations whereby the fitness

of individuals within populations increases when they can

better tolerate those specific soil conditions (Ellis & Weis

2006; Fierer & Jackson 2006; Alvarez et al. 2009). Natural

gradients in soil pH have been shown to influence the com-

munity composition of bacteria, fungi and arbuscular

mycorrhizal fungal communities (Dumbrell et al. 2010).

Substrate age and soil development represent other strong

gradients, which influence nutrient availability (Vitousek

2004). With low soil nutrient availability, it has been

demonstrated that there will be selection for symbiotic

mutualists and a slow cycling microbial community. Low

nutrient availability may also select for small leaves, high

nutrient use efficiency, slow growth rates, long foliar life

span, high nutrient resorption and recalcitrant plant tissues

that decay slowly. Such recalcitrant plant tissues may lead

to continued low soil nutrient availability and thus a con-

sistent selective pressure on plant traits that convey fitness

advantages under these environmental conditions. Rein-

forcement of these patterns may ultimately lead to local

adaptation to low soil nutrient availability (sensu Bertness

& Callaway 1994).

In order to test the importance of feedbacks in mediating

plant evolutionary processes, we designed a mathematical

model and undertook a simple, spatially explicit, individ-

ual-based model simulation to study the evolution of PSF

along an environmental gradient (e.g. soil pH). Spatially

explicit individual-based models are used extensively in

both ecological and evolutionary biology (Gavrilets 2004;

Gavrilets & Vose 2005 and references therein; de la Pe~na

et al. 2011). While other models of evolution along

gradients exist, here we examine the evolution of feedbacks

that are created by niche construction (i.e. the effects of

organisms on their environment and the evolutionary

legacy effects that result; Odling-Smee et al. 2013). PSF

studies are increasingly performed, and a general experi-

mental approach is well defined (Kulmatiski et al. 2008;

van der Putten et al. 2013) however, little is known about

how feedbacks affect the evolution of plant traits over time.

We examined how feedbacks and plant traits are affected

by gene flow (seed dispersal), strength of selection and the

strength of niche construction because previous literature

has shown that both gene flow and the strength of selection

are important factors determining when trait divergence

and local adaptation can occur (Hendry, Taylor & McPhail

2002; Lenomand 2002). Niche construction is one of the

simplest mechanisms that can cause plant–soil feedbacks.

We study only one species and a very simple genetic archi-

tecture (two quantitative plant traits, x and y; one that

responds to soil conditioning and one that causes soil con-

ditioning, respectively) because we need to first understand

possible evolutionary dynamics in simple systems if we hope

to gain intuition about more complex systems. Our objec-

tives are to mathematically quantify the evolutionary role

of niche construction in plant–soil feedbacks. We do this by

describing the relationship between the sign and magnitude

of PSF along environmental gradients with a spatially expli-

cit, individual-based simulation model to examine the con-

ditions under which plant traits diverge, plants become

locally adapted and when niche construction evolves and

PSF occur. Specifically, we hypothesized that: (i) niche con-

struction can cause PSF and that variation in environmen-

tal gradients impact the magnitude and direction of PSF

and (ii) a plant’s ability to construct a niche can evolve and

lead to altered environmental conditions, where plant traits

diverge. Our results provide an evolutionary framework for

understanding the occurrence of positive and negative PSF

on the landscape and for elucidating when this might occur.

These results also improve our understanding of the evolu-

tionary outcomes of plant–soil linkages and highlight direc-

tions for future research.

Materials and methods

MODEL DESCR IPT ION

Plant–soil feedbacks have most often been studied in ecological

theoretical models to understand patterns of diversity and plant

community structure, with only a few studies addressing possible

evolutionary consequences (Bever, Westover & Antonovics 1997;

Eppinga et al. 2011). For example, exponential growth models,

resource competition models and stochastic cellular automata

models have all been utilized to determine the sign and magnitude

of PSF and whether plant species can coexist (or not) across gradi-

ents of time, space and competition for limiting nutrients in the

presence or absence of feedbacks (Bever, Westover & Antonovics

1997; Molofsky et al. 1999; Molofsky et al. 2002; Eppstein et al.

2006; Mangan et al. 2010; Eppinga et al. 2011; Fukami &

Nakajima 2011; Fukami & Nakajima 2013). Evolutionary conse-

quences of feedbacks have been addressed by Bever, Westover &

© 2013 The Authors. Functional Ecology © 2013 British Ecological Society, Functional Ecology, 28, 55–64

Plant–soil feedback and evolution 57

Antonovics (1997), where the temporal and spatial scale of dis-

persal and scale of plant–soil interactions were found to alter

plant fitness of the next generation. Similarly, Eppinga et al.

(2011) modelled the effects of and feedbacks between leaf litter

that alter the nutrient environment and evolutionary change on

the competitive ability of an invasive grass. They found that litter

feedbacks and evolutionary change together could lead to the

dominance of an invasive species as feedbacks accelerated evolu-

tionary change to more competitive genotypes with different nutri-

ent quality. We expanded these previous studies that model how

positive and negative feedback can change community dynamics

through space and time by focusing on heritable changes in plant

traits and plant abilities to condition soils across selective gradi-

ents when the strength of selection, degree of gene flow (seed dis-

persal) and degree of conditioning (represented as niche

construction) are manipulated. These factors, to our knowledge,

have not previously been incorporated into feedback models.

Specifically, we explored mathematical and simulation models

whereby a single plant species evolves on a gradient of soil condi-

tions created by plant traits. Plant–soil feedback in these models

appears as a result of interactions between a plant and its soil over

time and space as a consequence of a plant’s ability to change

characteristics of the local soil, whether by modifying soil chemis-

try (e.g. pH), the amount or quality of soil organic matter or

through alterations of the soil biota (e.g. accumulation of patho-

gens/parasites or mutualists). Table 2 describes the model parame-

ters and descriptions used for both the mathematical and

simulation models.

To focus on mechanisms, we considered only one plant species

evolving along an environmental gradient. We assume that each

plant genotype is characterized by two traits. The first is an eco-

logical trait (x) that is directly under selection through a simple

matching mechanism, such as plant pH sensitivity in response to

soil pH. The probability of germination of a seed depends on how

closely its genotype (the value of x) matches the soil pH, with

respect to its optimum. If the mismatch is large (i.e. plants with a

preference for basic soil pH germinating in acidic soil are mal-

adapted or deviate from an adaptive peak), the seed will have low

rates of germination and thus lower fitness. If the mismatch is

small (i.e. adapted plants germinating in soil near their optimal

pH), the seed will have high rates of germination and high fitness

(i.e. it is well adapted to those conditions). If there is a complete

match (i.e. optimal pH), the seed will always germinate. We

assume that a genotype exists that is optimal for each value of soil

pH on the gradient. This assumption implies that it is possible to

have a perfectly adapted genotype (seed always germinates) to

each soil type. The second key factor in this model is the degree of

niche construction (y). This represents any plant trait that may

cause positive or negative PSF (in the pH example, this may be

foliar chemistry or root exudates that alter soil pH). Feedbacks

result when a seed has a different germination rate when planted

in soil conditioned by its own genotype (‘home’) than the same

soil conditioned with another genotype (‘away’), which in this

model occurs when plants can change their soil. When plants do

not change the soil, the conditioned soil will be the same as

unconditioned soil and feedbacks will not occur.

To address the hypothesis that niche construction can cause

PSF and to describe the relationship between the sign and magni-

tude of PSF along soil gradients, we sought a mathematical

expression for the dependence of the sign and magnitude of PSF

on a plant’s germination probability in unconditioned soil vs.

conditioned soil (i.e. plant-determined soil conditions) based on

the parameters described above (e.g. Table 2).

To address the second hypothesis, that a plant’s ability to

construct a niche can evolve and lead to altered environmental

conditions, under which plant traits diverge, we performed indi-

vidual-based simulations of plants evolving on a soil gradient over

time (i.e. after both 1000 and 10 000 generations). To illustrate

the model results, we interpreted them using a hypothetical sce-

nario with soil pH (although it would also be possible to use soil

biota, nutrient availability or other gradients that plants can mod-

ify, future work will examine these scenarios and mechanisms).

With this interpretation, niche construction would correspond to

the ability of a plant to change its soil by making it more or less

acidic (e.g. an Ericaceae species, such as Rhododendron spp., that

increases soil acidity; Wurzburger & Hendrick 2009). Specifically,

we took a spatially explicit individual-based modelling approach

to examine the roles of niche construction, seed dispersal and

selection on divergence of an ecological trait. The space in the sim-

ulation is represented by a 2D square grid (map). The grid consists

of L by L cells, where each cell contains one adult plant. Each cell

is characterized by a number between 0 and 1 called a ‘soil value’

(h0). Soil values for each cell are picked such that they create a

linear gradient across the map (ranging from 0 on the ‘left’ side of

the map to 1 on ‘right’ side; see Fig. S1 in Supporting Information

for the relationship between h0 and plant traits). Biologically,

different values of h0 represent one or multiple soil features that

are related to seed germination (e.g. soil pH). During one genera-

tion, (i) mature seed disperses to neighbouring cells, (ii) seed ger-

minates and grows depending on the match between the ‘x’ trait

and h in the cell, (iii) seedlings compete such that only one

matures in the cell, (iv) adult plants produce hermaphroditic flow-

ers, (v) flowers are pollinated by pollen from neighbouring cells or

by self pollination, (vi) adult plants produce seed and (vii) adult

plants change the cell’s h based on the ‘y’ trait. If the cell is empty,

h is set to the original conditions. We assume that a change to soil

Table 2. Model parameters utilized in both the mathematical and simulation models. Additional details of the simulation model are

included in the Supporting Information document

Range values Description

x 0–1 (0 = optimally adapted) Plant trait under selection. Ecological trait responsible for

determining the probability of seed germination

y 0–1 (0 = no niche construction) Plant trait that conditions soil. Trait related to ability of

a plant to modify soil

r 0�05 (high), 0�1 (intermediate), 0�2 (low) Strength of directional selection

m 0�1 (low), 0�5 (intermediate), 1�0 (high) Seed dispersal, representing gene flow

h 0–1 (0 = unconditioned soil) Soil value along a linear gradient related to seed germination.

The extent to which the soil changes depending on the plants y

(niche construction) trait and the unconditioned value (h = h0 + ƒ(y))b 0 (no niche construction), 1�0 (intermediate), 2�0 (high) Slope of the line relating h to ƒ(y) (i.e. ƒ(y) = b(y-1/2)). This slope

determines how fast niche construction changes with changing y traits

as well as the maximum amount that h can change due to the plant’s y trait

© 2013 The Authors. Functional Ecology © 2013 British Ecological Society, Functional Ecology, 28, 55–64

58 J. A. Schweitzer et al.

is the last event that happens in the generation, but since selection

acts on seed viability, the results will be the same if soils are chan-

ged by an adult plant before it produced flowers or sets seed.

Plant–soil feedback in the simulation model appears because a

change in soil affects the fitness of a genotype that will be present

in the cell in the next generation. During the course of simulation,

plants spread from the point of introduction (on right) across the

map, and by generations 1000 (and 10 000), the whole map is

populated by plants that differ with respect to their x and y phe-

notypic traits (see Figs S4 and S5 in Supporting Information for

visualizations of these maps).

Effect sizes were calculated on the simulation data to indicate

the relative importance of niche construction (from none to med-

ium and none to high) on the x and y traits over time and across

the soil values from h0 to h1. Standard effect sizes were calculated

using the mean trait values.

Results

PSF AND THE MATHEMAT ICAL MODEL

To address the hypothesis that niche construction can

cause PSF and describe the relationship between the sign

and magnitude of PSF along soil gradients, we sought a

mathematical expression for the dependence of the sign

and magnitude of PSF on a plant’s germination probabil-

ity in unconditioned soil vs. conditioned soil (i.e. plant-

determined soil conditions). We defined the strength of

plant–soil feedback as the natural logarithm of the ratio of

probability of germination in soil conditioned by the plant

of the same (‘home’) genotype to probability of germina-

tion in soil conditioned by different (‘away’) genotype

(Fig. 1 in the text). The strength of PSF in this model is

equal to:

PSF ¼ �ððfðy1Þ � fðy2ÞÞ=rÞðfðy1Þ þ fðy2Þ þ 2ðh0 � x1ÞÞeqn 1

where x1 is the value of the ecological trait of the plant

being tested in a PSF experiment (e.g. pH sensitivity),

f(y1) is the amount by which genotype (x1,y1) changes the

soil pH, f(y2) is the amount by which genotype (x2,y2)

changes the soil pH, h0 is the pH of unconditioned soil

and r is the strength of selection on the x trait.

PSF will be positive when x1 < (f(y1) + f(y2))/2 + h0and f(y1) < f(y2) or when x1 > (f(y1) + f(y2))/2 + h0and f(y1) > f(y2) and negative when x1 < (f(y1) +

f(y2))/2 + h0 and f(y1) > f(y2) or when x1 > (f

(y1) + f(y2))/2 + h0 and f(y1) < f(y2).

These inequalities tell us that PSF can be positive (or

negative) both when (x1, y1) genotypes can change the soil

pH by a large or a small value and that the sign of PSF

also depends on the pH of the unconditioned soil. For

example, if we observe positive PSF, the feedback can be

positive, either because a ‘home’ plant can change the soil

less strongly than the ‘away’ plant and the mismatch

between the ‘home’ plant and unconditioned soil is more

than the mean of the ability to change the soil of ‘home’

plant and ‘away’ plant ((f(y1) + f(y2))/2). Alternatively,

the ‘home’ plant can change the soil more than the ‘away’

plant, and a mismatch between the ‘home’ plant and

unconditioned soil is less than the mean of the ability to

change the soil of the ‘home’ plant and ‘away’ plant (this

is similar for negative PSF).

Equation (1) shows that the magnitude of PSF increases

with increasing (i) strength of selection (smaller r implies

stronger selection strength); (ii) a mismatch between an

unconditioned soil and the ecological trait of the ‘home’

(x1, y1) genotype (h0–x1); and 3) the differences between

the ability of ‘home’ and ‘away’ (x2, y2) genotypes to

change a soil. Plant–soil feedback does not depend on the

ecological trait of the ‘away’ genotype (x2) because by defi-

nition, to perform a PSF experiment, we must be able to

plant an ‘away’ genotype in order to create ‘away’ soil. On

the other hand, since we are testing performance of the

‘home’ genotype in different soils, the probability of germi-

nation of a ‘home’ genotype must depend on x1.

The magnitude and the sign of PSF tells us little about a

plant’s ability to change soil values (construct a niche) or

how adapted it is to unconditioned soil (see Figs S1 and

S2 in Supporting Information for an example when a plant

is and is not adapted to unconditioned soil to illustrate the

complex relationship of PSF on the model parameters).

0·0 0·2 0·4 0·6 0·8 1·0

0·2

0·4

0·6

0·8

1·0(a)

(b)

Genotype

Ger

min

atio

n pr

obab

ility A B C

A (Positive PSF) B (No PSF) C (Negative PSF)S

treng

th o

f PS

F

–0·6

–0·4

–0·2

0·0

0·2

0·4

Fig. 1. Schematic of plant-soil feedback (PSF) as a result of niche

construction. If seed germination rates are higher in soil condi-

tioned by a plant of the same genotype as the seed’s (‘home’ soil,

black line) than by a plant of a different genotype (‘away’ soil,

grey dashed line), positive PSF will occur. When there is no differ-

ence in germination rates, no PSF will occur (A). Negative PSF

occurs when seeds germinate more often in ‘away’ soil. In this

example, the black curve is the probability of germination of seeds

with different x trait values (genotypes) in the home soil

(hhome = 0�5). The grey dashed line is the probability of seed ger-

mination of seeds with different value of x trait in away soil, when

away soil differs from ‘home’ soil by 0�2 (haway = 0�7). Seeds of

genotype A will experience positive PSF, seeds of genotype B will

experience no PSF, and seeds of genotype C will experience nega-

tive PSF. (b) The magnitude of PSF for the three different cases.

Genotypes: x = 0�5 (A), x = 0�61 (B) and x = 0�8 (C).

© 2013 The Authors. Functional Ecology © 2013 British Ecological Society, Functional Ecology, 28, 55–64

Plant–soil feedback and evolution 59

Plant–soil feedbacks can be large if the difference in the

ability to change the soil between two genotypes is large

and the strength of selection on an ecological trait is weak,

but PSF can also be large if an ecological trait (pH sensi-

tivity in this scenario) is under strong selection and the dif-

ference in ability to change the soil is small. Better

understanding of the mechanisms (e.g. abiotic vs. biotic)

causing PSF is therefore needed to understand how PSFs

change over time. Knowledge of the details concerning the

role of soil biota in mediating selection is therefore critical,

and the large number of studies showing the importance of

soil biota to PSF confirms this result (Packer & Clay 2000;

Klironomos 2002; Levine et al. 2006; Kardol et al. 2007;

Rout & Callaway 2009; Mangan et al. 2010; van de

Voorde, van der Putten & Bezemer 2012). Future work

will incorporate explicit biotic mechanistic components of

the feedback process.

EVOLUT ION OF NICHE CONSTRUCT ION , PSF AND

LOCAL ADAPTAT ION

Having mathematically shown the link between plant

traits, selection and the magnitude and direction of PSF,

we then used simulations to address the second hypothesis,

that a plant’s ability to construct a niche can evolve and

lead to altered environmental conditions that can drive

genetic divergence in plants. At least three mutually exclu-

sive possible outcomes are possible from these simulations:

(i) either a plant does not evolve the ability to alter soil

and feedbacks are not generated; (ii) a plant evolves the

ability to alter soils and feedbacks are generated; or (iii) a

plant evolves the ability to alter soils but feedbacks are not

generated.

Simulation results showed that plants can evolve the

ability to alter soils and that feedbacks can be generated.

Specifically, plants diverge with niche construction, and

both the strength of the selection on the x trait and the

degree of gene flow impact the magnitude of trait diver-

gence (Fig. 2). The strongest differences between models

with niche construction and models without it occur when

a soil changes strongly with respect to the y trait (high

niche construction), selection on the x trait is strong and

seed dispersal is intermediate (Fig. 2d). Using the pH

example, this would mean that changes by a genotype due

to a strong influence of a y trait on soil niche construction

can cause large changes in soil pH, that with intermediate

seed dispersal and strong selection of niche construction

on an x trait would result in evolutionary divergence of

trait x. The same patterns were observed after 10 000 gen-

erations, indicating that this phenomenon can persist over

time (see Fig. S6 in Supporting Information). Examination

of the long-term effects of feedbacks on the divergence of

the y (niche construction) trait (after 1000 and 10 000 gen-

erations) also indicates divergence (i.e. a trait responsible

for plant soil feedback can evolve; Figs 3 and S7 in

Supporting Information), but to a lesser extent than for

the x (response) trait.

Comparing the patterns of trait divergence with and

without niche construction suggests that plants can diverge

with respect to an ecological trait (trait x), such as pH sen-

sitivity, via both local adaptation and PSF (comparing the

line with no niche construction to the lines with two

degrees of niche construction; Fig. 2). However, the level

of divergence is different with niche construction than

without it and the relative effect size of divergence in the x

trait is larger with niche construction than without it (com-

paring no to high niche-construction dotted grey line, rela-

tive to medium niche construction, dashed grey line, on

Figs 2 and 3). The relative difference in effect sizes varies

on opposite sides of the map from where the seed was

introduced and is due to the fact that as plants colonize

the map, they change the soil gradient (due to the evolu-

tion of the y trait; Fig. 3), resulting in an evolutionary

feedback. With PSF (i.e. plants possess particular y traits

that can change the soil pH), we observed over time a

reduction in the range of values of the ecological trait x

(pH sensitivity). This change is most prominent in recently

invaded environments (left side of each plot). This suggests

that when there is no niche construction, the x trait might

diverge more and we might observe more different geno-

types with respect to the x trait. Those genotypes will be

limited to smaller ranges compared to the genotypes of

plants that can construct niches.

Discussion

Overall, the mathematical and simulation models support

the suggested data by illustrating that both negative and

positive PSF can be predicted with the tested evolutionary

variables (i.e. niche construction, selection, gene flow). Fur-

ther, a plant’s abilities for niche construction can evolve

and divergence in plant traits can occur with PSF. Changes

in soils or a plant’s location within the habitat can result in

maladaptation (reduced survival and fitness with mis-

matched conditions) and negative PSF. Specifically, the

model manipulating the degree of niche construction,

strength of selection and seed dispersal rate indicate that

niche construction can evolve and that divergence can occur

with niche construction as well as with local adaptation

(without niche construction, see below). The effect size

results, however, indicate that niche construction results in

larger divergence due to the fact that it changes the soil gra-

dient through the evolution of the y trait. Results show that

the greatest divergence in plant traits occurs when selection

is high, niche construction is high and seed dispersal is

intermediate. This suggests that the combination of strong

environmental gradients and genetic variation that leads to

strong niche construction can lead to selection for particu-

lar traits. When we remove niche construction (solid line,

Fig. 2), we still see divergence can occur simply due to

forces such as local adaptation (relative matching of soils to

traits) that do not involve feedbacks per se. This result sug-

gests that with niche construction, the divergence level may

be lower for the responding trait but higher for the

© 2013 The Authors. Functional Ecology © 2013 British Ecological Society, Functional Ecology, 28, 55–64

60 J. A. Schweitzer et al.

conditioning trait (opposite when there is no niche con-

struction), which suggests that species ranges with niche

construction should be higher. Moreover, these results indi-

cate that after multiple generations, plant phenotypes

change. However, with niche construction, the phenotype

values at the end of the simulation depend on initial condi-

tions, while phenotype values at the end of the simulation

do not depend on initial conditions when there is no niche

construction. While the model results shown here indicate

the prevalence of positive feedback with niche construction

that can lead to a broader species range (relative to a lower

range with no niche construction), negative feedbacks are

commonly demonstrated in empirical studies. This suggests

that more work is required to elucidate the relative role of

positive and negative PSF, local adaptation and PSF in

empirical studies. It also demonstrates that niche construc-

tion can be critical to the process and may be particularly

important under certain environmental conditions that can

lead to evolutionary ‘hotspots’ (sensu Thompson 2005). One

important future direction for PSF research, therefore, is to

understand under which conditions feedback effects can lead

to high plant divergence in traits and under what conditions

simple matching patterns occur. Moreover, understanding

these patterns across landscapes will have large conse-

quences for elucidating co-evolutionary dynamics (among

plant and soil communities) and widespread patterns of

plant divergence that would not ordinarily be understood

with traditional plant population dynamic models.

The process of niche construction, in the context of

plant–soil linkages, whereby plant traits influence soil

physical, chemical or biological properties, indicates that

plants can have an extended phenotype that can alter soils

and influence other interacting species. An extended phe-

notype occurs when genetic variation for traits in one spe-

cies affects the fitness or performance of another species

(or many species, Whitham et al. 2006; Wade 2007; Bailey

2012), as has been shown in a variety of habitats and

model systems (Bailey et al. 2009; Hersch-Green, Turley &

Johnson 2011). Niche construction, the changes that

organisms bring to their environments over time, is grow-

ing in importance in evolutionary biology as it recognizes

that organisms impact their environment and have legacy

affects over time. Niche construction is becoming more

widely appreciated as an important evolutionary force in

eco-evolutionary dynamics in natural systems (Laland &

Sterelny 2006; Odling-Smee et al. 2013). A frontier in PSF

studies, therefore, is to understand the diverse mechanisms

by which niche construction occurs and the role of direct

or indirect genetic effects (Wolf et al. 1998) for plant evo-

lutionary and co-evolutionary relationships across land-

scapes. Strong gradients exist in soils, from large-scale

nutrient gradients to local gradients in soil pH and biota

due to niche construction that can lead to both positive

and negative PSF. Building on the concepts and model

described above, and the evolutionary responses inherent

in these patterns, the model indicates potential patterns

whereby both positive and negative PSF may be expected

to occur.

Studies demonstrating both negative and positive PSF

in patterns of community succession (Kardol, Bezemer &

0·0

0·2

0·4

0·6

0·8

1·0

X

Strong selection Intermediate selection Weak selection

Low

dis

pers

al

0·0

0·2

0·4

0·6

0·8

1·0

X

Inte

rmed

iate

dis

pers

al

0·0 0·2 0·4 0·6 0·8 1·0

0·0

0·2

0·4

0·6

0·8

1·0

X

θ0 θ0 θ0

0·0 0·2 0·4 0·6 0·8 1·0 0·0 0·2 0·4 0·6 0·8 1·0

Hig

h di

sper

sal

Niche Construction:

HighMedNone

(a) (b) (c)

(d) (e) (f )

(g) (h) (i)

Fig. 2. Plants can diverge, with respect to

an ecological trait (trait x) that responds to

plant-mediated niche construction traits

after 1000 (and 10 000 see Fig. S6 in

Supporting Information) generations. The

relative difference in divergence of trait x is

the greatest when the niche construction

potential (b) is high, seed dispersal is inter-

mediate and selection on x is strong (panel

d). The black dotted and dashed lines rep-

resent strong and weak niche construction,

respectively, relative to the full line, which

represents no niche construction. Compari-

sons of the lines with and without niche

construction indicate that the divergence

level of x traits varies and that with niche

construction, positive feedbacks typically

occur. Grey lines at the bottom of each

panel indicate the relative effect size

between none and medium niche construc-

tion (dashed grey line) and none to high

niche construction (dotted grey line). These

lines indicate that the magnitude of the

niche construction effect is larger on the

opposite side of the map from which the

seed was planted, due to changes to the soil

gradient related to the evolution of the y

trait.

© 2013 The Authors. Functional Ecology © 2013 British Ecological Society, Functional Ecology, 28, 55–64

Plant–soil feedback and evolution 61

van der Putten 2006; van de Voorde, van der Putten &

Bezemer 2011) is just one arena that suggests a need for a

unifying framework that incorporates feedback concepts at

larger scales, including evolutionary ones. Fundamentally,

and in its simplest form, positive PSF (enhanced fitness

after soil conditioning) indicates adaptation, while negative

PSF (reduced fitness after soil conditioning) indicates

maladaptation (Crespi 2000; Thompson, Nuismer &

Gomulkiewicz 2002). Questions addressing trade-offs and

relationships between positive and negative feedbacks

show that PSF can be an evolutionary process. Moreover,

the positive effects on biodiversity that often emerge from

negative PSF (and vice versa) are considered a conse-

quence of maladaptation (or adaptation) to soil condi-

tions, which broadens our perspective on PSF and

biodiversity studies. It may also represent an overlooked

biodiversity hypothesis, which suggests patterns of biodi-

versity may be due to species interactions mediated by

PSFs. Much more work is required to test this concept,

especially in the context of interactions with the soil biota.

The model utilized plant-induced changes to soil abiotic

factors, but the evolutionary responses of associated biota

may be less clear than in plants, due to the extraordi-

narily high biodiversity of soil organisms and the indirect

effects that mediate trophic interactions. Major questions

remain regarding the details of these interactions, includ-

ing (co)evolutionary dynamics, among plants and both

the above- and below-ground interacting biota. To date,

most studies have shown the importance of soil organisms

in creating PSF, but the majority of these studies treated

soils categorically as live vs. sterilized soil (Klironomos

2002; Rout & Callaway 2009; Mangan et al. 2010; Felker-

Quinn, Bailey & Schweitzer 2011; van de Voorde, van der

Putten & Bezemer 2012). Consequently, with only a few

exceptions, we know very little about which species or

groups are responsible for the creation of PSF effects in

plants (see Packer & Clay 2000, 2004; Reinhart & Clay

2009) or whether plants can select for genetic change in

soil communities, especially given the asymmetries

between plants and microbes in species richness, genera-

tion times and genetic recombination mechanisms.

Another important direction for future research, there-

fore, is to determine not only the identity and function of

interacting soil communities but also whether soil com-

munities respond to plants primarily by changes in com-

munity structure and density or by genetic changes within

component populations (i.e. evolved in response to PSF).

We did not address divergence in the soil biota or direct

and indirect genetic covariance among interacting individ-

uals that may persist through time in this model, but

acknowledge the importance of exploring this in future

work, especially with respect to pathogens and microbial

mutualists since their evolutionary dynamics may be the

most tractable.

Conclusions

Overall, the examples and model results reported here have

highlighted the potential consequences of PSF for plant

evolutionary processes and raised specific research

0·0

0·2

0·4

0·6

0·8

1·0

Y

Strong selection Intermediate selection Weak selection

Low

dis

pers

al

0·0

0·2

0·4

0·6

0·8

1·0

Y

Inte

rmed

iate

dis

pers

al0·0 0·2 0·4 0·6 0·8 1·0

0·0

0·2

0·4

0·6

0·8

1·0

Y

θ0 θ0 θ0

0·0 0·2 0·4 0·6 0·8 1·0 0·0 0·2 0·4 0·6 0·8 1·0

Hig

h di

sper

sal

Niche Construction:HighMedNone

Fig. 3. Simulation results suggest that

niche construction traits (y) can also

diverge (change phenotypes) over time

(1000 and 10 000 generations; see also Fig.

S7 in Supporting Information), indicating

that the ability to construct a niche can

also evolve. The relative difference in diver-

gence of trait y is the greatest when the

niche construction potential (b) is high,

seed dispersal is intermediate and selection

on y is strong (panel d), although the range

of divergence is smaller than in x traits (see

Fig. 2). The black dotted and dashed lines

represent strong and weak niche construc-

tion, respectively, relative to the full line,

which represents no niche construction.

Similar to Fig. 2, grey lines at the bottom

of each panel indicate the relative effect size

between none and medium niche construc-

tion (dashed grey line) and none to high

niche construction (dotted grey line). These

lines indicate that the magnitude of the

niche construction effect is larger on the

opposite side of the map from which

the seed was planted, due to changes to the

soil gradient related to the evolution of

the y trait.

© 2013 The Authors. Functional Ecology © 2013 British Ecological Society, Functional Ecology, 28, 55–64

62 J. A. Schweitzer et al.

questions that will further clarify the linkages between

plant–soil feedbacks and evolutionary processes across

taxa. This simple model is the first, to our knowledge, that

demonstrates many of the evolutionary processes that the

empirical data suggest. Utilizing an example of changes

and selective responses to soil pH via plant niche construc-

tion and the fitness consequences of the matching or mis-

matching of soil conditions to a plant’s ability to survive

in altered soils, the model demonstrates that there are evo-

lutionary consequences to plant–soil linkages via feed-

backs. As highlighted above, much more work is required

in natural systems to understand the broader implications,

mechanistic conditions and ultimate consequences for spe-

cies divergence and patterns of diversity that these results

imply. Addressing these frontiers will aid in our under-

standing of the evolutionary consequences of plant–soil

linkages and feedbacks and will contribute to a framework

for better understanding potential evolutionary outcomes

of species interactions in a changing global environment.

Acknowledgements

Special thanks to Paul Armsworth and to the anonymous reviewers whose

comments and suggestions significantly improved the manuscript. Funding

for the project came from the University of Tennessee.

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Received 14 May 2013; accepted 1 October 2013

Handling Editor: Charles Fox

Supporting Information

Additional Supporting information may be found in the online

version of this article:

Fig. S1. Strength of plant-soil feedback (PSF) when the x trait of

the ‘home’ plant (with genotype x1, y1) perfectly matches the

unconditioned soil (x1 = 0�5, h0 = 0�5, b = 1�0, r = 0�05).Fig. S2. Strength of plant-soil feedback (PSF) when the x trait of

the ‘home’ genotype does not match an unconditioned soil

(x1 = 0�1, h0 = 0�7, b = 1�0, r = 0�05).Fig. S3. Seed germination probability (pg) for seeds with different

x trait values in cells where soil value (h) is 0�5 (top) and 0�3(bottom).

Fig. S4. Snapshots of 100 9 100 map showing the spatial distribu-

tions of x, y and soil h traits at three time steps during the simula-

tion (at generations 1500 and 1000), with niche construction.

Fig. S5. Snapshots of 100 9 100 map showing the spatial distri-

butions of x, y and soil h traits at three time steps during the

simulation (at generations 1500 and 1000), with niche

construction.

Fig. S6. The mean trait x value across the soil gradient after

10 000 generations is very similar to the situation after 1000 gen-

erations (Fig. 2 in text) suggesting that differences in divergence

between cases with and without niche construction can persist

over time.

Fig. S7. The mean trait y value across the soil gradient after

10 000 generations is very similar to the situation after 1000 gen-

erations (Fig. 3 in text) suggesting that differences in divergence

between cases with and without niche construction can persist

over time.

Table S1. Change of soil due to niche construction (function f

(y) = b (y – ½)) for different values of y and b.

© 2013 The Authors. Functional Ecology © 2013 British Ecological Society, Functional Ecology, 28, 55–64

64 J. A. Schweitzer et al.