Plant community diversity alters the response of ecosystem multifunctionality to multiple global change factors

doi:10.21203/rs.3.rs-3022339/v1

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Plant community diversity alters the response of ecosystem multifunctionality to multiple global change factors

https://doi.org/10.21203/rs.3.rs-3022339/v1

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Biodiversity is hypothesized to mitigate global change impacts on ecosystem multifunctionality in terrestrial ecosystems. However, potential mechanisms through which biodiversity maintains ecosystem multifunctionality under global change remain unclear. We grew 132 plant communities with two levels of plant diversity, crossed with treatments based on ten global change factors. All global change factors negatively impacted ecosystem multifunctionality, but impacts were stronger in high than low diversity plant communities. We explored potential mechanisms for this unexpected result, finding that the inhibition of selection effects (i.e., covariance between yield of low diversity plant communities and the change in yield in high diversity plant communities) contributed to sensitivity of ecosystem multifunctionality to global change. Specifically, global change factors decreased the abundance of novel functional plants (i.e., legumes) in high but not low diversity plant communities. Moreover, negative impacts of global change on ecosystem multifunctionality were also mediated by increased relative abundance of fungal plant pathogens (identified from metabarcoding of soil samples) and their negative relationship with the abundance of novel functional plants. Taken together, our experiment highlights the importance of protecting high diversity plant communities and legumes, and managing fungal pathogens, to the maintenance of ecosystem multifunctionality when facing complex global change.

Biological sciences/Ecology/Biodiversity

Biological sciences/Ecology/Community ecology

Biological sciences/Plant sciences/Plant ecology

biodiversity

ecosystem functioning

fungal pathogens

selection effects

complementarity effects

niche

novel functional plants

Terrestrial ecosystems provide multiple concurrent ecosystem functions (multifunctionality), such as primary productivity, nutrient cycling, and litter decomposition^{1, 2}. With industrial and economic development, complexities associated with multiple global change factors (e.g., climate change, biological invasions, nutrient deposition, pollution) have increased uncertainty around predicting their impacts on terrestrial ecosystems^{3, 4}. For example, the impacts of a single global change factor can differ among multiple ecosystem functions, while different global change factors will have variable impacts on a single ecosystem function^{2, 5, 6}, highlighting that the relationship between ecosystem multifunctionality and multiple global change factors is complex⁷. Although recent studies have shown that many ecosystem functions are inhibited by global change factors^{8, 9}, some ecosystem functions are promoted, such as the positive impacts of increased temperatures, nitrogen deposition and CO₂ concentration on aboveground primary productivity^{10, 11}. One approach to deal with these complexities and variable impacts is through the consideration of ecosystem multifunctionality, which encompasses the overall response of multiple ecosystem functions¹². However, few studies have used controlled experiments to compare how ecosystem multifunctionality changes in response to multiple rather than single global change factors⁴, an important step to increase understanding of the relative severity of impacts of multiple global change factors on overall ecosystem functioning (multifunctionality), as well as any underlying mechanisms.

The impacts of global change factors on ecosystem multifunctionality can depend on biodiversity^{13, 14, 15, 16}, which generally has a positive relationship with ecosystem functioning, through the mechanisms of complementarity and selection effects^{17, 18}. Complementarity effects occur when high diversity plant communities have increased ecosystem functioning via complementarity (breadth and partitioning) of resource use^{17, 19, 20, 21}. Selection effects occur because high plant diversity increases the likelihood that a plant species associated with high ecosystem functioning will occur in the community^{20, 22, 23}. However, whether changes in complementarity and/or selection effects mediate the impact of global change factors on ecosystem multifunctionality has not been tested.

Furthermore, complementarity and selection effects are influenced by global change factors^{24, 25}, but the underlying mechanisms remain unclear. On the one hand, global change factors might strengthen complementarity effects and ecosystem multifunctionality by providing novel niches, increased niche width, and decreased niche overlap^{26, 27, 28} (Fig. 1a). For example, nitrogen deposition provides additional resources for plants, enlarging the resource niche to alleviate interspecific competition²⁹, decrease niche overlap³⁰, and maintain ecosystem functioning³¹. On the other hand, global change factors could weaken complementarity effects and ecosystem multifunctionality by reducing available niche space and increasing plant competition for limited resources^{32, 33} (Fig. 1b). Regarding selection effects, high plant diversity increases the probability of a species being present that can support high ecosystem multifunctionality³⁴. Moreover, any species that disproportionately contributes to differences in ecosystem multifunctionality between communities subjected or not to global change factors can be considered “novel functional species”, which might play an important role in selection effects under global change³⁵. If these novel functional species are resistant to global change factors, then this could suggest that differences in ecosystem multifunctionality between communities with low and high biodiversity might be based on selection effects (Fig. 1a). At the same time, because high diversity communities have a higher probability of containing these novel functional species than low diversity communities, this might mean that the resistance of ecosystem multifunctionality to global change factors is also higher. Conversely, if novel functional species are sensitive to global change factors, the result would be the opposite³⁶, with ecosystem multifunctionality more sensitive to global change factors in high diversity communities. Therefore, it remains unclear whether high community diversity confers resistance or sensitivity of ecosystem multifunctionality to global change factors, whether this occurs via changes in complementarity or selection effects, and the potential mechanisms underlying these changes³⁷.

An often overlooked impact of global change factors are their effects on plant-associated fungal communities^{38, 39}, which influence plant growth and ultimately ecosystem functioning via antagonistic and mutualistic interactions⁴⁰. For example, fungal plant pathogens alter litter decomposition, nutrient cycling, and inhibit plant productivity and flowering^{41, 42}. Moreover, fungal plant pathogens can mediate the relationship between plant diversity and ecosystem functioning via their strong impacts on plant fitness and resulting changes in relative abundances of plant species in plant communities⁴³. If global change alters the relative abundance of fungal plant pathogens and this in turn impacts plant groups that provide high ecosystem functioning and/or resistance to global change factors, ecosystem multifunctionality may also be impacted³⁵. Therefore, changes in the relative abundance of fungal plant pathogens might be a previously overlooked yet important mediator of the relationship between biodiversity and ecosystem multifunctionality under global change.

To investigate the relationship and mechanisms through which plant community diversity influences the sensitivity of ecosystem multifunctionality to global change factors, we conducted a greenhouse experiment where low and high diversity plant communities were subjected to ten global change factors: nitrogen deposition, soil salinity, drought, plant invasion, simulated grazing, oil pollution, plastics pollution, antibiotics pollution, heavy-metal pollution and pesticide pollution. We measured nine ecosystem functions to assess ecosystem multifunctionality and used plant aboveground biomass data to quantify changes in complementarity and selection effects (based on the additive partitioning method¹⁷), and niche width and overlap (based on Levin’s niche width index⁴⁴ and the Schoener niche overlap index⁴⁵, respectively), in response to multiple global change factors. We specifically investigated:

(1) Whether high diversity plant communities had higher resistance of ecosystem multifunctionality to multiple global change factors compared with low diversity plant communities.

(2) Whether global change factors affect the relationship between plant diversity and ecosystem multifunctionality via changes in complementarity and/or selection effects. We predicted that if complementarity effects were important, the impacts of multiple global change factors would be related to changes in plant niche width and overlap. Alternatively, if selection effects were important, the impacts of multiple global change factors would be related to changes in the abundance of novel functional plants and relative abundance of fungal plant pathogens.

Ecosystem multifunctionality was more sensitive to global change factors in high compared with low diversity plant communities

All global change factors negatively impacted ecosystem multifunctionality in both low and high diversity plant communities (all P < 0.026, Fig. 2). However, the average response index of ecosystem multifunctionality was 30% more sensitive to global change factors in high diversity than in low diversity plant communities (F = 19.21, df = 1, P < 0.001, Fig. 2). Results for individual global change factors are presented in the Supplementary Results and Fig. 2.

Global change factors reduced selection but not complementarity effects in plant communities

Selection effects were 60% lower on average in plant communities subjected to global change factors than in unaffected control communities (F = 13.52, df = 1, P < 0.001, Fig. 3b). In contrast, global change factors did not significantly alter complementarity effects (F = 1.67, df = 1, P = 0.203, Fig. 3a). Results for individual global change factors are presented in the Supplementary Results and Fig. 3.

Global change factors affected niche width and overlap, abundance of novel functional plants and pathogen relative abundance

Global change factors negatively impacted niche width and niche overlap in both low and high diversity plant communities (P < 0.001 for all t-tests; Fig. 4a,b). However, the average response index of niche width was 157% more sensitive to global change factors in low diversity than high diversity plant communities (F = 28.88, df = 1, P < 0.001, Fig. 4a). In contrast, the average response index of niche overlap did not differ between low and high diversity plant communities (F = 1.45, df = 1, P = 0.285, Fig. 4b). Results for individual global change factors are presented in the Supplementary Results and Fig. 4.

Chenopodiaceae spp. were identified as the most parsimonious set of species that influenced ecosystem multifunctionality without global change (explaining 50% of the variance in ecosystem multifunctionality), while Chenopodiaceae spp. and Fabaceae spp. were identified as influential plants with global change treatments (explaining 45% of the variance in ecosystem multifunctionality). Therefore, Fabaceae spp. (i.e., G. soja and M. officinalis) were identified as novel functional plants that mediated changes in ecosystem multifunctionality in communities subjected to global change factors. Global change factors negatively impacted the abundance of novel functional plants in both low and high diversity plant communities (all P < 0.001, Fig. 4). However, the average response index of the abundance of novel functional plants was 40% more sensitive to global change factors in high diversity than in low diversity plant communities (F = 19.32, df = 1, P < 0.001, Fig. 4c).

Global change factors negatively impacted the relative abundance of fungal plant pathogens, but only in low diversity plant communities (t = 4.65, df = 1, P < 0.001, Fig. 4b). The overall response index of fungal pathogen relative abundance did not differ between low and high diversity plant communities (F = 0.94, df = 1, P = 0.332, Fig. 4d).

Novel functional plants and fungal pathogens mediated the impacts of global change factors and plant diversity on ecosystem multifunctionality

The SEM supported that plant community diversity (positive) and global change factors (negative) had opposite direct relationships with ecosystem multifunctionality, although the negative relationship with global change factors was more than twice as strong (Fig. 5). Plant community diversity also had a positive indirect relationship with ecosystem multifunctionality, mediated by its positive relationship with the abundance of novel functional plants, which in turn had a strong positive relationship with ecosystem multifunctionality. In contrast, global change factors had a negative indirect relationship with ecosystem multifunctionality that was mediated by its negative direct relationship with the abundance of novel functional plants. Moreover, global change factors also had a positive direct relationship with the relative abundance of fungal plant pathogens, which in turn had a negative direct relationship with the abundance of novel functional plants, and therefore an indirect negative relationship with ecosystem multifunctionality (Fig. 5). Finally, the negative relationship between the response indexes of fungal pathogen relative abundance and the abundance of novel functional plants was only observed in high diversity plant communities (Extended Data Fig. 1).

Contrary to prevailing theory, our experiment showed that ecosystem multifunctionality was more sensitive to the impacts of global change factors in high diversity compared with low diversity plant communities. This result suggests that high plant diversity may not mitigate negative impacts of global change factors on ecosystem multifunctionality, which we demonstrate might result from reduced selection effects through decreased abundance of novel functional plants (i.e., legumes, Fabaceae: Glycine soja and Melilotus officinalis). Moreover, global change factors inhibited the abundance of novel functional plants by promoting fungal plant pathogens, which might contribute to the sensitivity of ecosystem multifunctionality to global change factors in high diversity plant communities. Our study is the first to examine the response of ecosystem functionality to multiple global change factors, and to investigate potential mechanisms underlying differences in resistance of ecosystem functionality between low and high diversity plant communities. Below we discuss the implications of our results for understanding of how plant communities respond to complex global change.

It is generally thought that high diversity communities are more resistant to environmental changes⁴⁶ and that ecosystem functioning in high diversity communities is less impacted by global change³⁷. Contrary to theory and prevailing evidence, we found that ecosystem multifunctionality was more sensitive to global change factors in high diversity than in low diversity plant communities. Previous studies have identified two possible explanations for why ecosystem functioning should be more resistant to global change factors in high compared to low diversity communities. First, in stressful environments (i.e., global change), interspecific competition could be reduced or even switch to facilitation in high diversity plant communities^{47, 48} (i.e., increased complementarity effects). Second, the probability of high functioning species being present in a plant community increases with higher diversity (i.e., increased selection effects) under global change ⁴⁹. However, we found that the response index of niche overlap to global change factors did not differ between high and low diversity plant communities (Fig. 4b), suggesting that plant competition might be not alleviated as expected in high diversity plant communities. Moreover, in our experiment, Chenopodiaceae species (Su. glauca and Su. salsa) were the dominant species across high and low diversity plant communities that were both affected and unaffected by global change factors, indicating that high functioning species were present in all communities. Therefore, in our experiment, changes in plant competition and dominant species were inconsistent with predictions based on previous studies, which may have contributed to the high sensitivity of ecosystem multifunctionality to global change factors in high diversity plant communities.

Global change factors consistently reduced selection effects, meaning that they reduced the relative abundance of species with disproportionally high contributions to ecosystem multifunctionality of plant communities^{17, 50}. We suggest that this reduction in selection effects might explain why ecosystem multifunctionality of high diversity plant communities was more sensitive to the impacts of global change factors¹⁸. This explanation is further supported by the abundance of novel functional plants (identified as the leguminous plants G. soja and M. officinalis) suffering stronger negative effects from global change factors in high compared with low diversity plant communities. Legumes promote nitrogen cycling, primary productivity and other ecosystem functions^{51, 52}, and previous studies have shown that legumes and their symbiosis with nitrogen-fixing rhizobia bacteria are sensitive to global change^{53, 54, 55}. Moreover, this result was consistent with those of a species richness experiment by Jia et al. (2020)³⁵, who showed that legumes contributed mostly to selection effects, which in turn influenced positive diversity effects on ecosystem functioning. Therefore, the more sensitive response of novel functional plants (rather than of dominant species) in high compared with low diversity plant communities might contribute to reductions in selection effects and ecosystem multifunctionality under global change.

We present evidence that fungal plant pathogens also contributed to the impacts of global change factors on ecosystem multifunctionality. We found that global change factors promoted the relative abundance of fungal plant pathogens in our experiment, potentially due to global change factors inducing physiological stress on host plants and decreasing their resistance to fungal pathogens^{56, 57}. Moreover, we also observed a negative relationship between the response index of relative abundance of fungal plant pathogens and the response index of the abundance of novel functional plants (i.e., legumes), but only in high diversity plant communities. Novel functional plants disproportionately contributed to ecosystem multifunctionality, and therefore, through impacting novel functional plants, fungal pathogens also indirectly contributed to the impacts of plant diversity and global change factors on ecosystem multifunctionality. Our results emphasize the importance of interactions between the aboveground plant community and belowground fungal taxa on ecosystem multifunctionality under global change.

Although ecosystem multifunctionality of high diversity plant communities was highly sensitive to the overall impact of multiple global change factors, the responses of ecosystem multifunctionality to individual global change factors were variable. However, ecosystem multifunctionality was more sensitive to most global change factors (with the exception of nitrogen deposition) in high compared with low diversity communities. The contradictory result for nitrogen deposition might be explained by nitrogen deposition also having a more negative impact on niche width in high compared with low diversity plant communities. Taken together, these mixed effects indicate that the impacts of global change factors on ecosystem multifunctionality are complex⁵⁸, and that interactions between multiple global change factors might counteract or intensify the effects of single global change factors on ecosystem multifunctionality in natural ecosystems. Therefore, studies that investigate the interactive effects of multiple global change factors on ecosystem multifunctionality will be an important future research direction, especially as global change is only predicted to worsen in the future^{4, 59, 60}.

Although impacts varied among individual global change factors, ecosystem multifunctionality was more sensitive to overall impacts from multiple global change factors in high diversity compared with low diversity plant communities. We show that this higher sensitivity might be due to weakened selection effects, as global change factors reduced the abundance of novel functional plants, such as legumes, in high diversity plant communities. Moreover, fungal plant pathogens also mediated the negative effects of global change factors on ecosystem multifunctionality through their inhibition of legumes in high diversity plant communities.

The increasing complexity of global change threatens the planet with biodiversity loss, posing a dire risk to ecosystem functioning^{34, 61}. Our results demonstrate that ecosystem multifunctionality is especially sensitive to global change in high diversity plant communities, which also support multiple ecosystem functions^{37, 62} (Extended Data Fig. 3), further highlighting the importance of protecting high biodiversity ecosystems⁶³. Therefore, we suggest that researchers and practitioners interested in the management of ecosystem multifunctionality under global change should prioritize the protection of high biodiversity ecosystems and sensitive but novel functional plants, such as legumes, as well as monitoring and managing the abundance of fungal plant pathogens.

Location and study species

The experiment was carried out in a greenhouse (daily mean temperature of 30 ℃ and air humidity maintained at ~ 85% by ventilating fan) at Baimiao Experimental Station, Shandong University, China (36°23′10″ N, 120°36′44″ E). We selected two representative species for each of four plant families that commonly co-occur in the Yellow River Delta⁶⁴: Gramineae (Eleusine indica (L.) Gaertn and Setaria viridis (L.) Beauv.); Chenopodiaceae (Suaeda glauca Bunge and Suaeda salsa (Linnaeus) Pallas); Compositae (Crepis bonii Gagnepain and Xanthium strumarium L.); and Fabaceae (Glycine soja Sieb. et Zucc. and Melilotus officinalis (L.) Pall.). We selected two plants per family because this allowed us to minimize genetic differences between the two types of low diversity plant community (see experimental design below). Seeds for each plant species were collected from the Yellow River Delta Field Experiment Station (37°51′9″ N, 118°48′53″ E) in September to October of 2020. All seeds were stored at 4 ℃ in a seed storage cabinet (CZ-300FC, TOP Instruments Ltd., China) until the experiment began.

Experimental design

Plant communities were established in planting boxes (52 cm long × 35 cm wide × 30 cm high) that contained a soil mixture comprising 18.5 kg of field soil from Shandong University Garden and 13.5 kg of peat growing medium. Coarse litter and stones were first removed from the field soil with a 5 mm sieve. In March 2021, seeds were planted at a depth of 2.5 mm following the experimental design described below. Each plant community was sown at a rate to produce ~ 1000 total sprouting seedlings, based on background germination rates measured prior to starting the experiment (Supplementary Methods, Table S1).

Plant communities were planted with two levels of plant diversity (high, low). The high diversity treatment included all eight plant species, whereas the low diversity treatment included four plant species, comprising one randomly selected plant species from each of the four families. To control for species selection effects, two different plant communities were used for the low diversity treatment, such that one low diversity community included E. indica, Su. glauca, C. bonii, and G. soja, and the other low diversity community included the other four plant species: Se. viridis, Su. salsa, X. strumarium and M. officinalis. Thus, there were three types of plant communities, with two levels of plant diversity. One month after seedling germination, each type of plant community was crossed with eleven global change treatments: nitrogen deposition, soil salinity, drought, plant invasion, grazing, oil pollution, plastics pollution, antibiotics pollution, heavy-metal pollution, pesticide pollution, and a control community where no treatments were applied. Details of the protocol for each global change treatment are described in Table 1 and the Supplementary Methods. In total there were 132 plant communities (3 plant community types × 11 global change treatments × 4 replicates). Each community was watered every two days except for those exposed to the drought treatment.

Table 1

Experimental design of each global change factors on low and high diversity community. Details of the protocol for each global change treatment are described in the Supplementary Methods.
Global change factors	Experimental treatment
Nitrogen deposition	Added the equivalent of 100 kg N ha^− 1 year^− 1 to communities
Soil salinity	Added NaCl to increase soil salinity to 4.0 dS m^− 1
Drought	Communities watered every four days, compared to every two days for the control treatment
Plant invasion	Transplanted 20 seedlings of invasive Erigeron canadensis after one month of growth
Grazing	Seedlings mown to 10 cm above the ground after one month of growth
Oil pollution	Added 25 g of petroleum hydrocarbon
Plastics pollution	Added 20 g of polycarbonate and 20 g of polystyrene
Antibiotics pollution	Added 0.575 g of amoxicillin, 0.075 g of norfloxacin, 0.145 g of erythromycin and 0.055 g of sulfadimidine
Heavy metal pollution	Added 7.536 g of Pb(CH₃COO)₂ (plumbum) and 15.625 g of CuSO4·5H₂O (cuprum)
Pesticide pollution	Added 8 g of imidacloprid

Measurement of ecosystem multifunctionality

To assess ecosystem multifunctionality, we first measured nine separate ecosystem functions in each community, including primary productivity, microbial biomass, nitrogen cycling, phosphorus cycling, carbon cycling, floral abundance, litter decomposition, crown interception, and soil enzyme activity. Measurement protocols are described in the Supplementary Methods.

We then used the average values method to quantify ecosystem multifunctionality⁶⁵ (Table S2), following the methods of Maestre et al (2012)¹⁴.

$$Ecosystem multifunctionality=\frac{1}{F}\sum _{i=1}^{F}g\left(r\left({f}_{i}\right)\right)$$

$F$ is the total number of ecosystem functions that were measured; ${f}_{i}$ is the measurement of a single ecosystem function i; $r$ is the mathematical function to transform ecosystem function i to a positive value (see below); and $g$is the transformation to standardize the ecosystem function i. Data for ecosystem functions for which lower values reflect a more desirable aspect of the ecosystem (i.e., lower soil total nitrogen, nitrate, ammonium, and phosphorus content) were multiplied by − 1 (inverted around the 0 mean) to maintain directional change with other ecosystem functions, such that a decline from their desirable state corresponds to increasingly negative values⁶⁶. This transformation allowed any general differences among communities in multifunctionality to be more easily assessed. All ecosystem function data were standardized by maximum transformation (all values in [0,1]), and these standardized data were then used to calculate the ecosystem multifunctionality metric.

Measurement of complementarity and selection effects

Complementarity effects occur when the net yield (i.e., biomass) in high diversity plant communities exceeds that predicted based on yield measured in low diversity plant communities, due to resource partitioning and positive interactions. Selection effects occur when species with higher-than-average yields in low diversity plant communities dominate the biomass of high diversity plant communities. To calculate complementarity and selection effects in our experiment, we used the additive partitioning method, following the approach of Loreau and Hector ¹⁷.

$$\varDelta Y={Y}_{O}-{Y}_{E}=N\stackrel{-}{\varDelta RY}\stackrel{-}{\varDelta M}-N\text{cov}\left(\varDelta RY,M\right)$$

$$\text{C}\text{o}\text{m}\text{p}\text{l}\text{e}\text{m}\text{e}\text{n}\text{t}\text{a}\text{r}\text{i}\text{t}\text{y} \text{e}\text{f}\text{f}\text{e}\text{c}\text{t}\text{s} = N\stackrel{-}{\varDelta RY}\stackrel{-}{\varDelta M}$$

Selection effects = $N\text{cov}\left(\varDelta RY,M\right)$$=$$N\stackrel{-}{\varDelta RY}\stackrel{-}{M}-({Y}_{O}-{Y}_{E})$

We first calculated the diversity effect in high diversity plant communities, which was the sum of the complementarity effect and selection effect. A positive diversity effect meant that the observed yield in high diversity plant communities (${Y}_{0}$) exceeded the “expected yield” (${Y}_{E}$) (i.e., $\varDelta Y>0$). Expected yield was calculated as the weighted (by the initial relative abundance of plants, i.e., the properties t of seed sown, in high diversity plant communities) average of the yields in low diversity plant communities. Complementarity effects were calculated by multiplying the number of community types in low plant diversity communities ($N$), the average deviation from expected yield of the plants in the high diversity plant communities ($\stackrel{-}{\varDelta RY}$), and the average yield of each type of low diversity plant community ($\stackrel{-}{M}$). A positive complementarity effect meant that the yield of plants in the high diversity plant community was higher than expected based on the weighted average yield in the corresponding low diversity plant community. Selection effects were estimated as the covariance between the yield of community types in low diversity plant communities and the change in relative yield in high diversity plant communities (i.e., $N\text{cov}\left(\varDelta RY,M\right)$), which could also be calculated as the difference between diversity effects and complementarity effects (i.e., $N\stackrel{-}{\varDelta RY}\stackrel{-}{M}-\varDelta Y$). A positive selection effect meant that species with higher-than-average yields in low diversity plant communities dominated the biomass of high diversity plant communities. Specifically, the calculation method for data from our experiment was as follows:

$${Y}_{0}={M}_{high}={M}_{high1}+{M}_{high2}$$

$${Y}_{E}=\frac{{M}_{low1}+{M}_{low2}}{N}$$

$$\stackrel{-}{M}=\frac{{M}_{low1}+{M}_{low2}}{N}$$

$$\stackrel{-}{\varDelta RY}=\frac{\left({M}_{high1}-{M}_{low1}\right)+\left({M}_{high2}-{M}_{low2}\right)}{N}$$

${M}_{low1}$ and ${M}_{low2}$ represent aboveground biomass (total aboveground biomass of the four plant species) from the two types of low diversity plant communities. ${M}_{high1}$ and ${M}_{high2}$ represent aboveground biomass of the four plant species from the high diversity plant community that correspond to the same four plant species in the low diversity plant community. N was the number of community types that make up the low diversity plant communities, a constant of 2.

Measurement of niche width and overlap

We estimated niche width and niche overlap based on Levin’s niche width index⁴⁴ and the Schoener niche overlap index⁴⁵ using the “spaa” package⁶⁷ in R (v 4.0.1)⁶⁸ based on the relative abundance of plant species in each replicate at harvest.

$$Levin’s niche width index=\frac{1}{\sum _{\dot{j}=1}^{r}{\left({P}_{ij}\right)}^{2}}$$

$$Schoener niche overlap index=1-\frac{1}{2}\sum _{j=1}^{\gamma }\left|{P}_{ij}-{P}_{kj}\right|$$

${P}_{ij}$ and ${P}_{kj}$ represent the relative abundance of species i and k in each replicate plant community in each treatment j.

Fungal community

To quantify the effects of global change factors and plant community diversity on the relative abundance of fungal plant pathogens, 25 g of soil was collected at harvest from 5–10 cm below the soil surface using a spade (sterilized in 75% ethanol) and following the five-point sampling method (five individual 5 g samples collected from points in a quincunx [i.e., at the community center and halfway towards each of the four corners] and then pooled together for analysis). Soil samples were stored at -80 ℃ until DNA extraction for fungal community analysis by high-throughput sequencing. The DNA extraction, library construction, and bioinformatic analysis protocols are described in detail in the Supplementary Methods. Fungal plant pathogens were identified from the fungal sequencing data by using a consistent approach to query the FUNGuild database of fungal functional guilds⁶⁹: any taxa assigned as “probable” or “highly probable” plant pathogens were used for subsequent analyses, including taxa that also belonged to other guilds.

Measurement of response index to global change factors

We used a response index to represent the impacts of global change factors on ecosystem multifunctionality and other variables that were measured in our experiment:

Response index = ln(X_{with global change factor}) – ln(X_{without global change factors})

Where X represented measurements of ecosystem multifunctionality, niche width, niche overlap, the abundance of novel functional plants (see below) and the relative abundance of fungal plant pathogens. If the value of the response index was > 0, this meant that global change factors had a positive effect on the variable of interest. If the response index was < 0, this meant that global change factors had a negative effect. After calculation of the response index to each individual global change factor in low or high plant diversity communities, the response index data was averaged across all global change treatments to represent the average (overall) response index to global change factors for low and high diversity plant communities.

Statistical analysis

Response of ecosystem multifunctionality to global change factors in high and low diversity plant communities

To test whether the response index for overall and individual global change factors was different from 0, a series of one-sample t-tests with FDR (False Discovery Rate) correction were used. To test whether the impact of overall and individual global change factors on ecosystem multifunctionality differed between high and low diversity plant communities, we used multiple linear mixed models (e.g., response index for ecosystem multifunctionality ~ plant community diversity) with FDR correction. To account for the non-independence of low diversity plant communities of the same community type, we included community type (e.g., low diversity plant community 1, low diversity plant community 2, high diversity plant community) as a random effect. If the absolute value of the response index for one parameter was significantly higher for high than low diversity plant communities, we interpreted this as meaning that this parameter had greater sensitivity or reduced resistance to global change factors in high than low diversity plant communities (Fig. 1).

Mechanisms of diversity effects under global change factors

We assessed potential mechanisms that mediate the impact of plant diversity on the response of ecosystem multifunctionality to global change factors, including complementarity and selection effects. To test whether complementarity and selection effects differed between communities that were affected or unaffected by overall and individual global change factors, we again used a series of linear mixed models with FDR correction.

To identify novel functional plants, we obtained the minimally adequate set of species that impacted ecosystem multifunctionality with or without global change factors by using a stepwise AIC (Akaike Information Criterion) model selection approach to fit linear additive models to ecosystem multifunctionality, following Hector and Bagchi (2007)¹³. Two initial full models explaining ecosystem multifunctionality with or without global change factors contained main effects for all plant species. Each species was removed from the models in turn to obtain multiple models, for which AIC was calculated. The AIC values of the resulting models were compared, and the plant species whose exclusion led to the greatest improvement (reduction) in the AIC value was permanently removed from the model. This model selection process was repeated until dropping any of the remaining species increased AIC, at which point we considered that the minimally adequate model had been identified. This analysis was conducted using the “multifunc” package^{65, 70}. Any plant species that differed between the two minimally adequate sets of species with and without global change factors were defined as novel functional plants that played an important role in ecosystem multifunctionality⁶⁵. To test whether high and low diversity plant communities differed in how overall and individual global change factors impacted the response indexes of niche width, niche overlap, abundance of novel functional plants, and relative abundance of fungal plant pathogens, we again used a series of linear mixed models with FDR correction. Before the analyses, Kolmogorov-Smirnov and Levene tests were conducted to assess normality and homogeneity of residuals, respectively, and these assumptions were satisfied

Relationships between ecosystem multifunctionality and plant diversity with global change factors

To test hypothesized relationships among plant diversity, global change factors, and ecosystem multifunctionality (Extended Data Fig. 2), we used a piecewise structural equation model (SEM)⁷¹. In the SEM, communities subjected to global change factors were represented by 1, and communities without global change factors (i.e., control communities) were represented by 0. Because the abundance of novel functional plants and the relative abundance of fungal plant pathogens were identified as contributing to the resistance of ecosystem multifunctionality to global change factors, these variables were also included in the SEM. We hypothesized that global change factors and plant diversity would directly influence ecosystem multifunctionality, and would also have indirect effects via changes in the relative abundance of fungal plant pathogens and the abundance of novel functional plants. Non-significant relationships in the theoretical model (Extended Data Fig. 2) were removed to optimize model fit, which was presumed adequate with a non-significant χ² test (P > 0.05), low root means square error of approximation (RMSEA < 0.08), and high comparative fit index (CFI > 0.90) in AMOS version 24.0 (Amos Development, Spring House, USA).

Data availability

Sequence data have been deposited in the NCBI GenBank Short Read Archive under accession number PRJNA970937. The data supporting the findings of this study are available in Figshare Database.

Acknowledgements

We thank all of the farmers for management of the Experimental Station and the postdoctoral innovation project of Shandong (2021033) for seed collection. This work was supported by the National Natural Science Foundation of China (No. U22A20558; 31970347; 32271588).

Author contributions

Z.W. Xu, G. Xiao and W.G. Guo designed the study and obtained funding. Z.W. Xu, Y. Hu, J.F. Wang and M.Y. Li conducted the experiment. Z.W. Xu conducted data analysis. Z.W. Xu, G. Xiao, X.N. Yu, W.J. Allen and W.G. Guo were involved in the interpretation of results. Z.W. Xu and G. Xiao drafted the manuscript with significant contributions to the writing from all co-authors. Z.W. Xu, G. Xiao and W.J. Allen edited the final manuscript, which was commented on and approved by all authors.

Competing interests

The authors declare no competing interests.

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Plant community diversity alters the response of ecosystem multifunctionality to multiple global change factors

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Abstract

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Introduction

Results

Discussion

Conclusion

Material and methods

Location and study species

Experimental design

Measurement of ecosystem multifunctionality

Measurement of complementarity and selection effects

Measurement of niche width and overlap

Fungal community

Measurement of response index to global change factors

Statistical analysis

Response of ecosystem multifunctionality to global change factors in high and low diversity plant communities

Mechanisms of diversity effects under global change factors

Relationships between ecosystem multifunctionality and plant diversity with global change factors

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Acknowledgements

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