Climate change driven shifts in plant-soil feedbacks – A meta-analysis

doi:10.21203/rs.3.rs-1548188/v1

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Climate change driven shifts in plant-soil feedbacks – A meta-analysis

https://doi.org/10.21203/rs.3.rs-1548188/v1

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Purpose

Climate change is expected to affect plant-soil feedbacks (PSFs), influencing plant community dynamics and, through this, ecosystem functioning. However, our knowledge of effects on the magnitude and direction of PSFs is limited, with considerable variability between studies.

Methods

We quantified PSF effect sizes associated with common climate change factors, specifically drought and warming, using a meta-analytical approach. We investigated whether effects were consistent across functional groups, life histories (annual versus perennial, native versus non-native), planting (monoculture, mixed culture) and experimental conditions (field, greenhouse/laboratory).

Results

Drought induced stronger negative PSFs relative to ambient conditions while warming had no main effect. The response to drought was largely driven by stronger negative PSFs in grasses, suggesting that grasses may be more sensitive to drought. Interestingly, drought induced negative PSFs only in non-native species, suggesting that native species may better adapted to tolerate water stress. By contrast, we found an opposite in pattern in response to warming which may then favour invasive species. Perennial herbs displayed stronger negative PSFs than annual herbs in response to drought. Mixed species communities displayed more negative PSFs than monocultures, independent of climate treatment. Finally, warming and drought treatment PSF effect sizes were more negative in experiments performed in the field than under controlled conditions.

Conclusion

We provide evidence that drought and warming can induce shifts in PSFs, which are dependent on plant functional groups, life history traits and experimental conditions. These shifts would be expected to have implications for plant community dynamics under projected climate change scenarios.

Climate change

drought

warming

plant functional group

life cycle

species origin

Plant-soil feedbacks (PSFs) refer to the ability of a given plant to alter soil abiotic or biotic conditions in ways that modify the growth of a plant subsequently growing in the same soil. Over the last three decades, PSFs have been increasingly recognized as important drivers of plant community assembly and through this ecosystem functioning (Bever 2003; van der Putten et al. 2016). PSFs are considered positive and negative when plants modify soils in ways that respectively enhance or reduce the performance of an individual of the same species subsequently grown in the same soil (Bever et al. 1997). There is now evidence that PSFs influence plant community structure and dynamics, plant succession and invasion processes (Bonanomi et al. 2005; Kardol et al. 2006; Klironomos 2002; Revilla et al. 2013). Moreover, there is also growing evidence that climatic and environmental factors influence plant-soil biotic interactions causing shifts in PSFs with implications for the future of plant population dynamics (Bardgett et al. 2018; Weidner et al. 2015; Wubs & Bezemer 2018). Accordingly, several recent studies have shown climate change induced shifts in PSFs related to both direct effects on the plant and indirectly effects driven by changes in the composition and activity of soil biota (Crawford & Hawkes 2020; Snyder & Harmon-Threatt 2019; Xi et al. 2018). However, our knowledge about how climate change drivers alter PSFs, and the potential implications for plant community dynamics, remains limited (van der Putten et al. 2016; Pugnaire et al. 2019).

Plant-soil feedbacks are induced via both abiotic and biotic pathways (Fig. 1). For instance, individual plants can increase their relative belowground carbon (C) allocation (Fig. 1, Pathway 1) which can enhance interactions with soil microbes, such as N-fixing bacteria and mycorrhizal fungi (Fig. 1, Pathway 4), resulting in a positive effect on plant biomass production through increased uptake of nitrogen (N) and phosphorus (P), respectively (van der Putten et al. 2016). Such beneficial associations promote positive feedbacks that may extend beyond the lifetime of an individual through a build-up of beneficial organisms (van der Putten et al. 2016; Revillini et al. 2016). Positive plant-soil biotic interactions may be particularly important in stressful environments, including under nutrient or water limited conditions (Lagueux et al. 2021; Rutten & Gómez-Aparicio 2018). Furthermore, climatic, and environmental conditions influence plant physiological and morphological traits (Fig. 1, Pathway 2) in ways that can affect ecosystem functions, such as litter decomposition and nutrient cycling (Fig. 1, Pathway 3), resulting in subsequent changes in plant performance due to changes in nutrient availability. For example, both heatwaves and drought have been shown to result in the production of more recalcitrant litter (i.e., increased C:N ratios of leaf litter, higher lignin concentration; Almagro et al. 2015) which is likely to slow down decomposition and reduce nutrient availability resulting in negative PSFs (Fig. 1). Moreover, plants are also exposed to pests and pathogens belowground (Fig. 1, Pathway 4) that negatively affects plant growth. For example, the accumulation of root pathogens can reduce the growth of individual plants as well as individuals subsequently growing in the same soil if they are sensitive to those specific pathogens causing negative PSFs (Bezemer et al. 2013; Domínguez-Begines et al. 2021). Similar effects are likely to occur aboveground in response to herbivory, but the broader effects of plant-herbivore interactions on PSFs are not well known and are difficult to predict given the greater mobility of herbivores (Heinze et al. 2020).

Despite a growing body of literature, it is not yet clear how climate factors, such as warming and drought, alter the magnitude and direction of PSFs (Fig. 2). There are three main non-mutually exclusive hypotheses about the drivers of climate effects on plant-soil feedbacks: 1) Change in climate modify plant inputs to soil via litter quantity and quality and root exudation influencing nutrient cycling; 2) Climate change either reduces or enhances the effect of species-specific pests and pathogens; and 3) Climate change disrupts or strengthens the interaction with beneficial microbes. In all cases, the outcome will depend on the climate change factor in question and the level of change (van der Putten et al. 2016). Warming generally enhances decomposition and metabolic rates of microbes (Fig. 2, Pathway 1a) which increases the availability of soil nutrients, thus promoting positive PSFs. However, the potential role of warming on PSFs is less clear in the context of beneficial microbes, such as arbuscular mycorrhizal fungi (AMF), as warming can increase (Rasmussen et al. 2020; Rillig et al. 2002) and decrease (Wilson et al. 2016; Zhang et al. 2021) AMF colonization. Indeed, warming may reduce beneficial microbial colonization (Fig. 2, Pathway 2a) if the plants have access to essential resources thus promoting negative PSFs. However, warming may result in water and nutrient limitation, which may promote root fungal colonization in order to get access to nutrients thus promoting positive PSFs (Rasmussen et al. 2020). Furthermore, warming generally promotes the density and activity of root-feeding soil fauna and increases root pathogen infection (Fig. 2, Pathway 3a) resulting in negative PSFs (Lu et al. 2015; Staddon et al. 2003; Wilson et al. 2016). By contrast, reduced rainfall or drought generally reduces litter decomposition and root exudation by decreasing the activity of decomposers and metabolic rates (Fig. 2, Pathway 1b), respectively, thus promoting negative PSFs. On the other hand, drought could increase mycorrhizal root colonization as the plant allocates more C belowground for nutrient access promoting positive PSFs (Fig. 2, Pathway 2b). Furthermore, drought may reduce pest and pathogen abundance, resulting in relatively more positive PSFs (Fig. 2, Pathway 3b) (Cheng et al. 2016). The role of aboveground herbivory is known to promote negative PSFs due to changes in leaf chemistry, such as shoot nitrogen concentration (Heinze et al. 2020); however, few studies have assessed the role of herbivory under manipulated climates; thus, herbivory is not considered in this meta-analysis (Fig. 2, Pathway 4).

Several general patterns regarding the occurrence of PSFs have been revealed. PSFs known to be species specific but appear to differ consistently across plant functional groups (Fry et al. 2018; Heinze et al. 2017; Kulmatiski et al. 2008). A growing body of literature has found that grasses and forbs generally show negative PSFs while woody species show neutral PSFs (Chung & Rudgers 2016; Cortois et al. 2016). The first meta-analysis assessing PSFs showed that they are predominantly negative at the species level and positive, or at least less negative, at the community level (Kulmatiski et al. 2008). PSFs have similarly been shown to depend on plant life cycle characteristics (annual and perennial) and species origin (native and non-native). Current literature suggests that native species may show negative PSFs due to increased pests and pathogens densities (Callaway et al. 2004; Meisner et al. 2013; van der Putten 2002). On the other hand, non-native species may escape from species-specific soil-borne pathogens in a foreign environment thus reducing negative plant-soil biotic interactions and promoting positive PSFs (Callaway et al. 2004; Meisner et al. 2013; Perkins & Nowak 2013; van der Putten 2002; Zhang et al. 2019). Species with annual life cycles tend to produce more negative PSFs relative to species with longer life cycles (i.e., perennial); however, the mechanisms underlying this pattern are still unknown (Kulmatiski et al. 2008). It is possible that long lived perennial species, such as shrubs and trees, might invest more in plant defence making them less sensitive to pest and pathogens than short lived species (Kulmatiski et al. 2008). How climate change influence these patterns is still unknown (Pugnaire et al. 2019).

Here, our aim was to assess the impact of elevated temperature (henceforth ‘warming’, ET) and reduced rainfall (henceforth ‘drought’, DT) on the magnitude and direction of PSFs. There were too few studies on other climate drivers, such as elevated CO₂, for these to be included in the meta-analysis. Synthesizing existing data will enhance our understanding of how warming and drought might modify PSFs and help predict the role of PSFs in shaping plant community dynamics in response to a changing climate. We specifically asked:

a) Do PSFs shift in response to warming and drought?

b) Do warming and drought effects on PSFs differ across plant functional types?

c) Do warming and drought effects on PSFs differ between annual and perennial species and native and non-native species?

d) Are PSFs dependent on experimental conditions (greenhouse/laboratory versus field)? And, lastly,

e) Do PSFs differ between species growing conditions (monoculture and mixture)?

Literature search and study selection

Meta-analytical data were collected following the guidelines of Field and Gillett (2010). We collected literature using targeted search keywords on Web of Science, Scopus, PubMed, and Google Scholar. The terms included were ‘plant soil feedback AND rainfall’, ‘plant soil feedback AND drought’, ‘plant soil feedback AND water availability’, ‘plant soil feedback AND temperature’, ‘plant soil feedback AND Carbon dioxide or CO₂’ ‘plant soil feedback AND global change AND experiments’ and ‘plant soil feedbacks AND climate change’. Based on search results (1990–2019) and the meta-analysis criteria, 52 papers were preliminary selected for the meta-analysis after carefully looking into the title and abstract.

In this meta-analysis, we focused on studies that assessed PSFs under both ambient and manipulated climate conditions using a known PSF experimental design. We collected data from papers where authors measured effects of drought (ambient versus drought) or increased temperature (ambient versus elevated) on plant biomass in a PSF experiment. We collected the following information about the experimental design for further analysis: plant functional group, plant life history (annual or perennial), plant origin (native or non-native), plant growing conditions (monoculture or mixture), and experimental approach (greenhouse/lab or field). Papers where the authors did not provide PSF data were discarded. Species biomass was recorded as the performance in its own soils and other species soil using typical PSF experimental designs (Bukowski et al. 2018; Wubs & Bezemer 2018).

Data collection and extraction

The main meta-analytical data were plant biomass in studies that manipulated temperature and/or rainfall using a PSF experimental approach where data for both ambient and manipulative conditions were provided. Due to the low number of studies, we combined studies that reported effects of reduced rainfall in any manner including experimental drought and drought legacies (legacies that had been established under long-term rainfall manipulation experiments). When a paper fulfilled the criteria (as discussed in the previous section), we recorded mean plant biomass, standard deviation (± SD) and sample sizes (N) for both ambient and manipulated climate. If standard deviation (SD) was not available, we calculated SD by multiplying standard error and square root of sample size (SE = SD/√N). The X_E, SD_E and N_E represent the experimental group (E) mean, standard deviation and sample size and X_C, SD_C and N_C for the control group (C) mean, standard deviation and sample size (Blankinship et al. 2011; Hedges et al. 1999; Kulmatiski et al. 2008; Lekberg et al. 2018).

Data were gathered directly from tables, or from figures using WebPlotDigitizer v. 4.1 (Rohatgi 2012), where possible or obtained from the corresponding author. Data were organized as plant biomass for a given species cultivated in its ‘home’ soil and the same species cultivated in ‘away’ soil under ambient and manipulated climate. Fourteen papers, including 4 unpublished datasets, were used for calculating effect sizes (Table S1). These studies produced a total of 182 individual effect sizes representing ambient and manipulated climate across all species. A key summary of each study used in the meta-analysis is presented in Table S2.

Meta-analysis

Choosing Hedges’ d over Cohen’s d

We calculated an unbiased mean PSF effect size as suggested by Hedges & Olkin (1985). The analyses of this meta-analysis were based on 14 independent studies (published and unpublished) that included 182 observations which is likely to cause a biased estimation of PSF effect size. Cohen’s d (effect size that described the standardised difference between two means) in particular tend to overestimate the effect size in studies with few observations (Hedges 1981). For this reason, we calculated mean effect size as Hedges’ d, which produces a very similar summary effect size but controls for this bias over Cohen’s d by multiplying with a correction factor (J) using Eqs. 1 and 2 where n₁ represents the sample size of control group (‘home’) and n₂ for experimental group (‘away’).

Eqn 1

To estimate bias corrected Hedges’ d, metacont function in the metafor R package were used (Viechtbauer, 2010) using following Eq. 2.

Eqn2

where d indicates Hedges’ d, µ₁ is the mean biomass of a species in the control (‘home’ soil) population and µ₂ is the mean biomass of a species in the experimental (‘away’) population. S represents the pooled standard deviation. We estimated an unbiased pooled standard deviation by following equation:

Eqn 3

where S₁ indicate standard deviation of control group (‘home’) and S₂ for experimental group (‘away’), n₁ represents sample size of control group (‘home’) and n₂ for experimental group (‘away) (Kulmatiski et al. 2008; Lekberg et al. 2018).

Model fitting

Multiple observations were extracted from a single study contradicting the assumption of study independence in meta-analyses (Field & Gillett 2010). Therefore, we performed multilevel model (hierarchical model) analyses using rma.mv function in the metafor package (Viechtbauer 2010) of R version 4.0.3 (R core team 2020) to reduce potential study bias. The multilevel hierarchical model that considered individual observations within papers independently fit better in most cases, resulting in lower Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values (Table S3-6). The multilevel model were fitted by using Hedges’ d and sample variance (v) as response variable, and paper and study number as random effects (Cheung 2014). The Knapp-Hartung adjustment were used for confidence intervals (CI). The mean PSFs effect sizes were considered significantly different from zero when 95% CI for Hedges’ d did not overlap zero.

Interpretation of effect size

The calculated effect size of PSF (Hedges’ d) was described according to the explanation of plant performance between home and away conditioned soils (Kulmatiski et al. 2008). Positive values of Hedges’ d indicate that species performed better in their own soils relative to soils cultivated by another species soil. Negative values of Hedges’ d indicate that species performed worse in their own soil relative to another species soil. Values close to ‘0’ indicate neutral PSFs when both positive and negative PSF cancel each other. Therefore, the size and sign of Hedges’ d is related to magnitude and direction of PSF, respectively (Kulmatiski et al. 2008).

Locating publication bias

We tested for publication bias by producing a histogram of effect size to check the data depression around zero, including a funnel plot (Begg 1994; Kulmatiski et al. 2008). We found that the distribution of effect size does not indicate a publication bias towards significant results (Fig. S1).

Moderator analysis

We specified five main moderators in this meta-analysis: plant functional group (grass, forb, legume, shrub, and tree), length of life cycle (annual and perennial), origin of species (native and non-native), growing condition (monoculture and mixture) and experimental condition (controlled environment and field). Therefore, we separately performed multi-level models to investigate the effects of each sub-moderator (e.g., grass) within individual moderators (e.g., plant functional group) on mean PSF effect size for each climate factor. We used Hedges’ d and the corresponding sample variance (v) of each effect size as the response variable, and paper and study number as random effects including Knapp-Hartung adjustment for confidence intervals. The rma.mv function in metafor was used to fit each model (Cheung 2014).

Overview of meta-data

From the 14 independent studies that met the criteria of our meta-analysis, we calculated 182 PSF effect sizes across two important climate change factors (warming and drought; Table S1). The vast majority of the PSF experiments were conducted in growth chambers or greenhouses (83%), with only a few completed under field conditions (17%). Similarly, 84% of the experiments used herbaceous species (grass, forbs, and legumes), with a large proportion of graminoids, and only 16% were woody species (shrubs and trees). Most studies assessed PSFs in monoculture (70%) with the remainder being mixed communities (30%). Finally, 69% of the species were perennial and 31% annual species, while there were about the same number of native and non-native species.

Overall effect of temperature and drought on PSFs

The mean PSF effect size was negative for all studies (d = − 0.408; 95% CI: -0.599 to -0.217; Z = -4.183, p < 0.0001; Fig. 3) but significant variation was found in feedback across studies (Q = 533.63; d.f. = 181; p < 0.0001; Table S3).

The mean PSF effect size across all studies that imposed ‘drought’ was similarly negative

(-0.526; 95% CI: -1.025 to -0.023; Z = -2.738, p = 0.006; Fig. 3; Table S3); however, PSFs were weakly negative and not significantly different from zero under ‘ambient water’ (d; -0.231, p = 0.113; Fig. 3; Table S3).

The mean PSF effect size for all studies that manipulated temperature was negative for both ‘ambient’ (-0.432; 95% CI: -0.830 to -0.033; Z = -2.123, p = 0.040) and ‘elevated temperature’ (d = -0.490; 95% CI: -0.940 to -0.040; Z = -2.135, p = 0.039; Fig. 3; Table S3).

Effects of temperature and drought on PSFs across functional groups

Although grasses displayed negative PSFs when grown under elevated temperature (-1.054; 95% CI: -2.067 to -0.041; Z = -2.039, p = 0.041; Fig. 4a; Table S4) and drought (-1.003; 95% CI: -1.951 to -0.054; Z = -2.072, p = 0.038; Fig. 4a; Table S5), mean PSF effect sizes were not different to ambient water and temperature. All other functional groups showed less negative or neutral PSFs under both ambient and experimental climate conditions (Fig. 4a).

We further pooled PSF effect sizes for ambient water and temperature and drought and elevated temperature considering two main functional groups, i.e., herbaceous (grass, forb, and legume) and woody plants (shrub). We found that drought drove a significant larger negative PSFs for herbaceous species (-0.509 CI: -0.879 to -0.139, p = 0.006) compared to ambient water (-0.169 CI: --0.445 to 0.106; Z = -4.003, p = 0.228; Fig. 4b). Likewise, elevated temperature caused significantly larger negative PSFs for herbaceous species (-0.534 CI: -0.99 to -0.07, p = 0.02) compared to ambient temperatures (-0.46 CI: -0.90 to -0.01, p = 0.04; Fig. 4b). Climate manipulation did not have significant effects on PSFs for woody species (Fig. 4b).

Effects of temperature and drought on PSFs depending on species origin and life cycle

Native species displayed negative PSFs irrespective of temperature manipulation (AT: -0.485, CI: -0.965 to -0.005; Z = -1.981, p = 0.047; ET: -0.633, CI: -1.098 to -0.168; Z = -2.670, p = 0.007) while non-native species showed neutral PSFs (Fig. 5a). Interestingly, non-native species displayed negative PSFs under drought conditions (-0.633, CI: -1.113 to -0.152; Z = -2.580, p = 0.009) while PSFs for native species were neutral (Fig. 5a).

Drought resulted in negative PSFs for perennial (-0.543, CI: -0.997 to -0.090; Z = -2.348, p = 0.018) species but not for annual species (Fig. 5b). No differences in PSFs of species with different life cycles were observed under temperature manipulation (Fig. 5b).

Effects of temperature and drought on PSFs depending on experimental and growing condition

PSFs were negative under both ambient (-0.9126, 95% CI: -1.6293 to -0.1959; Z = -2.495, p = 0.012) and elevated temperature (-0.9421, 95% CI: -1.6747 to -0.2094; Z = -2.520, p = 0.011) under field condition, while less negative PSFs were observed in experiments conducted in controlled environments.

PSFs were negative in experiments conducted in laboratory environment both under ambient water (-0.325, CI: -0.605 to -0.045; Z = -2.276, p = 0.022) and drought (-0.426, 95% CI: -0.741 to 0.112, Z=-2.657, p = 0.007; Fig. 6a) conditions. By contrast, for experiment performed under field condition, PSFs were negative (-1.597, CI: -2.399 to -0.795; Z = -3.904, p < 0.0001) under drought and neutral (1.431, 95% CI: -0.611 to 3.474) under ambient conditions (Fig. 6a).

Mixed cultures grown under ambient temperature showed negative PSFs (-0.559, CI: -1.107 to -0.011; Z = -2.001, p = 0.045) while monocultures showed neutral PSFs. The mixed culture displayed negative PSF (-0.605, CI: -1.220 to -0.009; Z = -1.931, p = 0.053) while monocultures showed neutral PSFs under elevated temperature (Fig. 6b). Drought caused negative PSFs in mixed cultures (-1.515, CI: -2.292 to -0.738; Z = -3.822, p = 0.0001) but neutral PSFs were observed for monocultures (Fig. 6b). Both mixtures and monocultures showed neutral PSFs under ambient water (Fig. 6b).

We provide evidence that climate change can modify plant-soil feedbacks in ways that will impact plant community dynamics under projected climate change scenarios (Pugnaire et al. 2019; Snyder & Harmon-Threatt 2019; van der Putten et al. 2016). Specifically, drought induced stronger negative PSFs in grasses while limited effects were observed in the other functional groups, indicating that grasses may be disproportionately impacted by drought. Moreover, perennial species showed stronger drought induced negative PSFs than annual species while non-native species showed stronger drought induced negative PSFs than native species (Fig. 5). Finally, the effects of drought and warming were stronger in PSF experiments conducted in the field than experiments in controlled conditions, possibly due to more realistic feedbacks between plants, soil biota and edaphic properties (Forero et al. 2019; Gundale & Kardol 2021; Kulmatiski & Kardol 2008). PSFs were more negative when species were grown in mixtures than in monocultures, likely driven by interspecific competition for resource such as water and space (Crawford & Knight 2017). This meta-analysis thus revealed that drought can promote negative PSFs, particularly in grasses, with some differences between functional groups, life history, origin, and experimental and growing conditions while warming appears to have less pronounced effects on PSFs.

Contrasting effects of drought and warming on PSFs

Drought induced stronger negative PSFs relative to PSFs observed under ambient water conditions while warming had limited effects on PSFs, with negative PSFs of similar effect sizes observed under ambient and elevated temperatures (Fig. 3). The contrasting response to warming and drought may relate to differences in their respective effects on soil nutrient availability and microbial associations (in ’t Zandt et al. 2019; Kaisermann et al. 2017; Fig. 2). Warming may promote positive interactions with plant and soil biota in resource limited systems if warming promotes beneficial microbes that help to access water and nutrients (Brookshire & Weaver 2015; Craine et al. 2012; Rasmussen et al. 2020). Conversely, warming may induce negative PSFs by reducing beneficial associations due to increased soil nutrient availability via increasing mineralization or by promoting faster life cycles of pathogenic microbes (Bennett & Klironomos 2019; van der Putten et al. 2016; Pugnaire et al. 2019). Other studies have found warming to reduce the colonization of mycorrhizae in grasses (Zhang et al. 2021) and flowering herbs (Wilson et al. 2016) as plants are less dependent on beneficial associations due to increased availability of nutrients, while drought enhances mycorrhizal association to promote uptake of essential mineral nutrients (Chareesri et al. 2020). Therefore, the two climate change drivers are likely to have contrasting effects on soil nutrient availability and microbial associations which will be reflected by their effects on PSFs.

Climate change effects on PSFs on plants from different functional groups and with contrasting life history traits

Drought was hypothesized to induce stronger negative PSFs but negative PSFs in grasses were also expected in the ambient treatments (Kulmatiski et al. 2008). We found that grasses displayed strong negative PSFs under drought conditions but less negative under ambient water indicating drought induced shifts in feedbacks (Fig. 4a). Similarly, forbs displayed weaker negative PSFs under drought conditions and neutral PSFs under ambient water conditions while neutral PSFs were observed in studies that simulated warming. Previous studies have suggested that drought induces weaker negative PSFs for forbs due to increased nutrient availability (Fry et al. 2018) and greater reliance on beneficial microbes (Kaisermann et al. 2017). However, the strong negative PSFs observed in grasses and relatively weaker negative PSF for forbs may be linked to their sensitivity to native pathogens (Lu et al. 2015). For example, grasses and forbs are more heavily affected by belowground enemies, such as plant-parasitic nematodes and pathogens, with their high root to shoot ratio, and larger root systems (Gleeson & Tilman 1994; Schenk & Jackson 2002; Wilsey & Polley 2006). The observed neutral PSFs for legumes are also consistent with the current literature (Cortois et al. 2016).

Legumes form mutualistic associations with nitrogen-fixing bacteria that promote positive PSFs balancing negative effects of pathogens, and the mutualism may be enhanced under drought and warming (Cortois et al. 2016). However, PSF experiments are largely dominated by grasses and forbs (Kulmatiski et al. 2008) with fewer studies investigating legume PSFs (Teste et al. 2017). Therefore, more studies need to consider legumes to determine whether climate change drivers will consistently influence PSFs. Shrubs and other woody species displayed neutral PSFs independently of climate manipulation which is also consistent with current literature (Kulmatiski et al. 2008). Long-lived species are generally less sensitive to belowground herbivores and pathogens via build-up of a strong protective sheath by ectomycorrhiza and ericoid mycorrhiza (Duchesne et al. 1989). They are also likely to invest more in belowground defence relative to short-lived grasses and forbs, thereby reducing negative PSFs from soil-borne pests and pathogens ( Bennett et al. 2017; Mariotte et al. 2018). However, more studies are needed to confirm this pattern under future climate scenarios.

Our results show that perennial species display strong negative PSFs under drought conditions while annual species showed weakened negative PSFs (Fig. 5b). Annual herbaceous species are more likely to suffer from negative PSFs due to host-specific pathogens, rapid vegetative growth, less investment in defence (Kardol et al. 2006), while perennial species may promote positive PSFs because they invest more in defence and form stronger mutualistic relationships with soil microbes (Callaway et al. 2004; Suding et al. 2013; van der Putten et al. 2002). The contrasting outcome for perennial species may be related to lower number of empirical studies available (i.e. less data points) including variation of soil microbial communities (de la Peña et al. 2010) and methodological contrast during PSF experiments (Brinkman et al. 2010). Moreover, generalization of previous finding is largely based on studies that did not manipulate climate. Therefore, more studies with species with contrasting life history traits conducted under different climate manipulation experiments are required to generalize feedback outcomes under future climate scenarios.

Climate change effects on PSFs of native and non-native species

Drought induced strong negative PSFs for non-natives but not for native species. By contrast, warming induced stronger negative PSFs in native species but not for non-natives (Fig. 5). A possible explanation is that drought disrupted the beneficial associations that non-native species rely on, or that they are more susceptible to drought stress than native species. On the other hand, differences between natives and non-natives for warming align with literature. Warming can increase the density of pathogens rapidly in conspecific soil which negatively impacts native species while non-native species may escape pathogens attack in new environments via enemy release mechanisms (Agrawal et al. 2005). Previous studies also indicate that native grasses and forbs are more sensitive to native soil pathogens than non-native species which can be exacerbated under warming (Hines et al. 2017; Kulmatiski et al. 2008; Meisner et al. 2014).

Climate change effects on PSFs in monocultures and mixtures

Drought and warming induced stronger negative PSFs in mixtures and less negative PSFs in monocultures (Fig. 6). Generally, species cultivated in monoculture tend to accumulate more pathogens than mutualists thereby promoting negative feedbacks (Klironomos 2002; Wang et al. 2020), while mixtures promote positive feedbacks due to an accumulation of beneficial microbes and dilution of negative effects of pathogenic microbes (Mommer et al. 2018). However, we observed stronger negative PSFs in the mixtures that might be linked to strong competition for nutrients and water under field condition (Teste et al. 2017). For example, drought can promote negative feedback by reducing nutrient availability resulting in increased competition, or by disrupting plant-microbe beneficial associations (Kaisermann et al. 2017). Moreover, if plant communities are composed of closely related species, they might accumulate more pathogens which will result in negative PSFs in mixtures (Mommer et al. 2018). On the other hand, plant communities composed of distantly related species representing a diversity of functional groups generally increase the diversity of beneficial microbes in communities and dilute the abundance of pathogenic microbes thus promoting positive PSFs (Mommer et al. 2018). However, more field studies are required where climate can be manipulated to generalize PSF response of plant communities under realistic environments.

Climate change effects on PSFs differ between laboratory and field conditions

Our study found that drought and warming induced strong negative PSFs when experiments were performed in the field and less negative under controlled environmental conditions. The contrasting outcomes are likely due to the presence of more realistic effects of herbivory both aboveground and belowground, greater competition among plants and soil physicochemical properties in field conditions as previously hypothesized (Ehrenfeld et al. 2005; Heinze et al. 2019; 2020; Snyder & Harmon-Threatt 2019). For example, aboveground herbivores have been shown to promote negative PSFs by reducing shoot biomass (Heinze et al. 2020) and indirectly via changing root morphological traits, such as increased production of thinner roots, that may change nutrient uptake (Heinze 2020). Likewise, belowground herbivores such as root feeding nematodes have been shown to promote negative PSFs in response to prolonged drought under field conditions (Hassan et al. in review). Such effects are unlikely to be reflected in experiments conducted in growth chambers or glasshouses. Moreover, competition for nutrients may also reduce plant growth, thereby changing PSF effect size between laboratory and field (Lekberg et al. 2018). Furthermore, PSF experiments conducted in a greenhouse or growth chambers use a wide variety of experimental approaches that are likely to cause contrasting outcomes (Gundale et al. 2017; Forero et al. 2019). A large number of PSF experiments conducted in a greenhouse or controlled environments use a small portion of live inoculum collected from the field (Kulmatiski et al. 2008; Kulmatiski & Kadrol 2008) but see (Chung et al. 2019; Kulmatiski 2019). These limited quantities may exclude common root herbivores or pathogens, such as plant parasitic nematodes, or symbionts that are important to plant growth under natural conditions (Cortois & De Deyn 2012; Crawford et al. 2019; De Long et al. 2018). More field studies are required to quantify the actual contribution of PSFs on plant population dynamics under changing climate.

Our results indicate that drought has negative effects on PSFs, with the effect particularly clear in grasses but consistent across all herbaceous species. Moreover, drought induced negative PSFs in perennial species but not annual species, and in non-native species but not in annual natives. Warming by contrast had limited effects on PSFs across all studies but induced negative PSFs in native species but not non-native species. Both drought and warming induced stronger negative PSFs in mixtures than monocultures. Similarly, drought and warming induced stronger negative PSFs when experiments were performed in the field than under controlled environmental conditions. We thus provide evidence that climate change will cause shifts in PSFs but that the effects differ among plant functional groups, life history strategy and species origin. Moreover, the effects on PSFs differ between monocultures and mixtures and with experimental conditions. The stronger effects under field conditions suggest that based on research so far, we may be underestimating the contribution of PSFs to plant community dynamics. Future research should assess the effects of global change drivers including elevated CO₂ across environmental and climatic gradients to better quantify global change effects on PSFs.

Acknowledgements

We like to thank authors who kindly provided the data for meta-analysis when necessary. KH was supported by Australian Commonwealth Government research training grant and study leave from Sylhet Agricultural University, Bangladesh. UNN was supported by funding from the Australian Research Council (DP150104199; DP190101968). The final version of this manuscript has been reviewed by an independent reviewer before submission (Giles M Ross).

Conflicts of interest

We have no conflicts of interest to disclose.

Author information

Affiliations

¹Hawkesbury Institute for the Environment, Western Sydney University, Penrith, New South Wales, Australia.

²Department of Entomology, Sylhet Agricultural University, Sylhet- 3100, Bangladesh.

³Department of Plant Pathology, Bangladesh Agricultural University, Mymensngh-2202, Bangladesh.

K. Hassan^1,2*, K. M. Golam Dastogeer³,Y. Carrillo¹AND U. N. Nielsen¹

Corresponding author: Kamrul Hassan

Author contribution

KH and UNN conceived and designed the meta-analysis. KH collected the data directly from author and online data base. KH conducted all formal analysis with input from KMGD and UNN. KH written first draft with direct supervisions from UNN and YC. All authors reviewed the chapter critically and approved the final version of the chapter.

Data availability

Data were deposited in figshare.com and will be shared publicly upon acceptance of manuscript.

Code availability

Not applicable

Supplementary information

ESM1

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Climate change driven shifts in plant-soil feedbacks – A meta-analysis

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Abstract

Figures

Introduction

Materials And Methods

Data collection and extraction

Meta-analysis

Choosing Hedges’ d over Cohen’s d

Model fitting

Interpretation of effect size

Locating publication bias

Moderator analysis

Results

Overview of meta-data

Overall effect of temperature and drought on PSFs

Effects of temperature and drought on PSFs across functional groups

Effects of temperature and drought on PSFs depending on species origin and life cycle

Effects of temperature and drought on PSFs depending on experimental and growing condition

Discussion

Contrasting effects of drought and warming on PSFs

Climate change effects on PSFs of native and non-native species

Climate change effects on PSFs in monocultures and mixtures

Climate change effects on PSFs differ between laboratory and field conditions

Conclusions

Declarations

References

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