Climate warming reduces the temporal stability of plant community biomass production — TEI-tagged view

Zhiyuan MapersName, Huiying LiupersName, Zhaorong MipersName, Zhenhua ZhangpersName, Yonghui WangpersName, Wei XupersName, Lin JiangpersName, Jin-Sheng HepersName (2017date). “Climate warming reduces the temporal stability of plant community biomass production.” Nature Communicationstitle·j.

Object of study — temporal stabilityterm·mth of alpine grasslandterm·key biomassterm·key under experimental warmingterm·dom and altered precipitationterm·key

Research question — how climate change affects ecological stability, and through which mechanisms

Contribution — field evidence that warmingterm·dom lowers biomassterm·key stability, which is set by dominant-species stability and asynchrony rather than diversity

Full text — tagged

The reference list is not part of the text we hold for this paper. Our copy was extracted from the publisher's page and the bibliography did not survive that extraction, so the article below ends before its references. Nothing has been removed by us.

Climate warmingterm·dom reduces the temporal stabilityterm·mth of plant community biomassterm·key production Abstract Anthropogenic climate change has emerged as a critical environmental problem, prompting frequent investigations into its consequences for various ecological systems. Few studies, however, have explored the effect of climate change on ecological stability and the underlying mechanisms. We conduct a field experimentterm·mth to assess the influence of warmingterm·dom and altered precipitationterm·key on the temporal stabilityterm·mth of plant community biomassterm·key in an alpine grasslandterm·key located on the Tibetan Plateauterm·key. We find that whereas precipitation alterationterm·dom does not influence biomassterm·key temporal stabilityterm·mth, warmingterm·dom lowers stability through reducing the degree of species asynchronyterm·dom. Importantly, biomassterm·key temporal stabilityterm·mth is not influenced by plant species diversity, but is largely determined by the temporal stabilityterm·mth of dominant speciesterm·key and asynchronous population dynamics among the coexisting species. Our findings suggest that ongoing and future climate change may alter stability properties of ecological communities, potentially hindering their ability to provide ecosystem services for humanity.

One of the basic attributes of an ecological system is its stability 1 2 . Since stable ecosystems are important for providing sustainable ecosystem functioning and services to humanity 3 , understanding the drivers of ecological stability has emerged as a pressing issue in a period when many ecosystems are experiencing significant anthropogenic change 4 5 6 7 . Much recent attention has focused on the temporal stabilityterm·mth of community biomassterm·key production, known to be influenced by several mutually nonexclusive mechanisms. First, changes in biodiversityterm·key may result in changes in biomassterm·key temporal stabilityterm·mth 6 7 8 . On the one hand, biodiversityterm·key may influence biomassterm·key temporal stabilityterm·mth because more diverse communities are more likely to contain species that are resistant to environmental fluctuations (the sampling effect 9 10 11 12 ). On the other hand, biodiversityterm·key can have a positive influence on biomassterm·key stability via promoting asynchronous population dynamics among species 13 14 15 . Second, absent biodiversityterm·key change, variation in the degree of asynchrony in population dynamics, in response to variation in abiotic and biotic conditions, may also lead to changes in community biomassterm·key stability 6 16 17 . Third, the population stability of dominant speciesterm·key may strongly influence community biomassterm·key stability, especially when communities are dominated by a small number of species 18 19 20 . Hence, climate change that alters biodiversityterm·key, the degree of species asynchronyterm·dom and/or the stability of dominant speciesterm·key may have the potential to alter the temporal stabilityterm·mth of community biomassterm·key production.

The average global temperature has increased by 0.065 °C per decade since 1880, accompanied by significant changes in precipitationterm·key patterns 21 . These rapid climate changes, unprecedented in human history, are likely to profoundly affect the functioning of Earth's ecosystems 22 23 . Climate warmingterm·dom has been demonstrated to influence community structure 24 25 26 and species interactions 27 28 29 that could potentially translate into changes in community biomassterm·key stability 30 31 32 . Likewise, changes in precipitationterm·key could alter community biomassterm·key production 33 , species diversity 34 and species relative abundance patterns 35 that may also have consequences for biomassterm·key stability 16 17 . Notably, the effects of climate warmingterm·dom and altered precipitationterm·key on community properties, including stability, may not be independent of each other, given that warmingterm·dom is expected to impose its strongest effect under drought conditions 33 36 37 . Studies manipulating both warmingterm·dom and precipitationterm·key to assess their influence on community biomassterm·key stability are vital for predicting ecosystem dynamics under future climate change scenarios.

Here, we report on a 5-year field experimentterm·mth investigating the influence of climate warmingterm·dom and altered precipitationterm·key on the temporal stabilityterm·mth of plant biomassterm·key production of an alpine grasslandterm·key on the Tibetan Plateauterm·key ( Supplementary Fig. 1 ). The Tibetan Plateauterm·key has an area of 2.5 million km 2 , with 64% of this region occupied by alpine grasslandterm·key that provides essential ecosystem services for humans living in the region 38 . As the world's highest plateau (4,500 m above sea level on average), the Tibetan Plateauterm·key has experienced more rapid climate warmingterm·dom (0.4 °C per decade over the past 50 years) than average, coupled with increasing and greater interannual variation in precipitationterm·key 38 39 . Climate warmingterm·dom and altered precipitationterm·key are known to influence net primary production 24 , biogeochemical cycles 38 , litter decomposition 40 and rangeland quality 41 in this region. However, their effects on the temporal stabilityterm·mth of this important ecosystem are unknown. We aimed to explore how future climate change would affect biomassterm·key temporal stabilityterm·mth and elucidate the role of potential mechanisms in driving the observed stability response to climate change. We show that climate warmingterm·dom reduces the temporal stabilityterm·mth of community biomassterm·key via reducing the degree of species asynchronyterm·dom, independent of precipitationterm·key effects. This result suggests that ongoing and future climate change may reduce the ability of the alpine grasslandterm·key and other similar ecosystems to provide reliable ecosystem services for humanity.

Results Plant community response to climate change Over the 5-year experimental period, warmingterm·dom did not influence plant community biomassterm·key (linear mixed-effects model: P =0.84; Fig. 1a ), but increased precipitationterm·key resulted in an average of 17.5% increase in plant community biomassterm·key ( P <0.001; Fig. 1a ). The effect of altered precipitationterm·key on community biomassterm·key, however, was stronger under warmingterm·dom, resulting in a significant warmingterm·dom × precipitationterm·key interaction term in the linear mixed-effects model ( P =0.02; Fig. 1a and Supplementary Table 1 ). Both warmingterm·dom and increased precipitationterm·key had negative effects (a reduction of 4.9% and 14.1%, respectively) on species richness and positive effects (an increase of 3.5% and 6.6%, respectively) on species dominance (all P <0.05; Fig. 1b,c ); their effects were largely independent of each other ( Fig. 1b,c and Supplementary Table 1 ).

Community temporal stabilityterm·mth and species asynchronyterm·dom Warmingterm·dom significantly reduced the temporal stabilityterm·mth of plant community biomassterm·key by an average of 23.2% (linear mixed-effects model: P =0.04; Fig. 2a ), whereas precipitation alterationterm·dom did not affect community biomassterm·key stability ( P =0.17; Fig. 2a and Supplementary Table 1 ). Likewise, warmingterm·dom significantly decreased species asynchronyterm·dom by an average of 11.9% ( P =0.01; Fig. 2b ), whereas precipitation alterationterm·dom had little effect on species asynchronyterm·dom ( P =0.37; Fig. 2b and Supplementary Table 1 ). No significant interactive treatment effects were observed for either biomassterm·key temporal stabilityterm·mth or species asynchronyterm·dom.

Dominant speciesterm·key stability Neither warmingterm·dom (linear mixed-effects model: P =0.23) nor precipitation alterationterm·dom ( P =0.27) affected dominant speciesterm·key stability ( Fig. 2c ). Species relative abundance was significantly positively correlated with their temporal stabilityterm·mth in all six treatments (linear regressions: all R 2 >0.18, P <0.01; Supplementary Fig. 2a ), indicating that dominant speciesterm·key were more temporally stable than less abundant species. Neither warmingterm·dom nor altered precipitationterm·key affected the relationship between species relative abundance and stability (analysis of covariance (ANCOVA) species relative abundance × treatment interaction: P =0.26, n =1,079; Supplementary Fig. 2a ). Similar results were obtained when rare species, whose high population variability (that is, low stability) may be potentially inflated by their low detectability, were excluded from the analysis (all R 2 >0.13, P <0.01; ANCOVA species relative abundance × treatment interaction: P =0.85, n =422; Supplementary Fig. 2b ).

Functional group stability When we classified species into functional groups (grasses, sedges, legumes and forbs), we found a change in the abundance of each group in response to experimental treatments ( Supplementary Fig. 3 ). However, the temporal stabilityterm·mth of each functional group was unaffected by experimental treatments (linear mixed-effects models: all P >0.05; Supplementary Table 2 ).

Ecological factors influencing biomassterm·key temporal stabilityterm·mth Linear regression revealed that community biomassterm·key temporal stabilityterm·mth was significantly positively correlated with species asynchronyterm·dom ( R 2 =0.53, P <0.001; Fig. 3a ), species richness ( R 2 =0.15, P =0.03; Fig. 3b ) and dominant speciesterm·key stability ( R 2 =0.58, P <0.001; Fig. 3c ), but not related to species dominance ( R 2 =0.04, P =0.30; Fig. 3d ). Among the four functional groups, only the stability of the grass functional group was significantly, positively, associated with community biomassterm·key stability (linear regression: R 2 =0.29, P <0.01; Supplementary Fig. 4 ). Structural equation modellingterm·mth (SEMterm·mth) showed that dominant speciesterm·key stability and species asynchronyterm·dom jointly explained 75% of the variation in community biomassterm·key stability, and that warmingterm·dom, but not precipitation alterationterm·dom, affected biomassterm·key temporal stabilityterm·mth ( Fig. 4 and Supplementary Fig. 5 ). The negative effect of warmingterm·dom on biomassterm·key temporal stabilityterm·mth was mainly through its negative effect on species asynchronyterm·dom ( Fig. 4 and Supplementary Fig. 5 ). Note that species richness, which showed positive association with biomassterm·key temporal stabilityterm·mth ( Fig. 3b ) and species asynchronyterm·dom ( Supplementary Fig. 6c ) in regression analyses, was eliminated from the SEMterm·mth as a significant predictor of biomassterm·key temporal stabilityterm·mth ( Fig. 4 , Supplementary Table 3 and Supplementary Fig. 5 ). Considering functional group stability in the SEMterm·mth did not significantly improve the fit of the model ( R 2 =0.77 and 0.75 in the SEMterm·mth model with and without considering grass stability, respectively).

Discussion Much of the Earth is experiencing climate warmingterm·dom and change in precipitationterm·key patterns. Ecologists have just begun to explore their consequences for ecological stability; three aspects of our study, however, distinguish it from the few previous studies on this topic. First, while the few studies of climate change effects on temporal stabilityterm·mth have considered either warmingterm·dom 31 32 or precipitationterm·key 16 17 , our study examines both warmingterm·dom and precipitationterm·key effects in a single experimentterm·mth. Second, our study was conducted on the Tibetan Plateauterm·key that, as the world's largest and highest plateau, is considered highly susceptible to climate change. Our study thus represents a rare exploration of climate change impacts on stability in an ecologically important but vulnerable habitat. Third and most important, our study demonstrated that climate warmingterm·dom could reduce biomassterm·key temporal stabilityterm·mth via reducing species asynchronyterm·dom, independent of precipitationterm·key effects.

Many studies, including field observations 42 43 , experimentsterm·mth that directly manipulated diversity 8 44 45 46 and theoretical models 47 48 49 , have shown that increasing species diversity tends to increase biomassterm·key temporal stabilityterm·mth. In our study, we also found a significant positive relationship between species diversity and biomassterm·key temporal stabilityterm·mth as revealed by linear regression ( Fig. 3b ). Given that climate warmingterm·dom reduced species diversity in our experimentterm·mth, as also found in other studies conducted in the same ecosystem 24 50 , one might think warming-induced diversity decline contributed to the decline in biomassterm·key stability under warmingterm·dom. However, species diversity was not retained in the SEMterm·mth as a significant predictor of biomassterm·key stability ( Fig. 4 ). On the other hand, increasing precipitationterm·key significantly increased species diversity, but precipitation alterationterm·dom did not affect biomassterm·key stability ( Figs 1 and 4 and Supplementary Fig. 5 ). One possible explanation for the lack of species diversity effect on biomassterm·key stability in our experimentterm·mth is that changes in species richness (2–4 species) under our experimental treatments were relatively small compared with community-level species richness (∼26 Sp.). Probably more importantly, most of the lost/gained species in response to our experimental treatments were rare species that accounted for only a small fraction of community biomassterm·key ( Supplementary Table 4 ). These rare species contributed relatively little to community biomassterm·key stability compared with species asynchronyterm·dom and the stability of dominant speciesterm·key (see below), making species diversity an unimportant driver of community biomassterm·key stability.

Asynchrony in population dynamics across species is a common feature of ecological communities 51 52 and could be attributed to asynchronous species responses to environmental fluctuations 2 15 . The most important finding of our study is that climate warmingterm·dom reduced species asynchronyterm·dom, translating into reduced community biomassterm·key stability under warmingterm·dom. Under climate warmingterm·dom, a few species, including Helictotrichon tibeticum and Medicago archiducis-nicolai , increased in abundance. However, the majority of species, which constituted 75% of community members, declined in abundance under warmingterm·dom, resulting in less asynchronous population dynamics. This result contrasts with that of a warmingterm·dom experimentterm·mth in a temperate steppe, where neither daytime nor nighttime warmingterm·dom altered species asynchronyterm·dom 32 . This discrepancy may be explained by temperature being a stronger limiting factor (that is, cold temperature constrains biological processes 29 ) in the alpine grasslandterm·key than the temperate steppe, translating into stronger species responses to the same amount of warmingterm·dom in the alpine grasslandterm·key. Probably also because of the limitation of plant growth by cold temperatures, we found that precipitation alterationterm·dom did not influence species asynchronyterm·dom or biomassterm·key stability. This contrasts with the results of several studies conducted in temperature grasslands, where increased precipitationterm·key was found to promote species asynchronyterm·dom 16 17 . Together, these results highlight the context dependency of how climate changes influence biomassterm·key stability and associated mechanisms, emphasizing the need to explore the combined effects of warmingterm·dom and altered precipitationterm·key in other ecosystems.

A growing body of evidence suggests that community biomassterm·key stability tends to show positive associations with the stability of dominant speciesterm·key 5 17 19 53 54 55 56 that may even constrain the effects of species diversity on biomassterm·key stability 57 . Our findings reinforce these ideas. An important characteristic of dominant speciesterm·key in our study is their greater temporal stabilityterm·mth than less abundant species ( Supplementary Fig. 2 ), a finding that has also been reported by several other studies 32 54 57 . Importantly, neither climate warmingterm·dom nor altered precipitationterm·key affected the temporal stabilityterm·mth of these dominant speciesterm·key that exhibited strong positive relationships with community biomassterm·key stability. In our experimentterm·mth, the two dominant speciesterm·key, Stipa aliena and Elymus nutans , accounted for approximately half (48.7%) of community biomassterm·key. They were relatively insensitive to environment fluctuations, probably because of their greater nutrient acquisition ability through well-developed root systems, and their greater light acquisition ability through taller canopy and larger specific leaf area in this alpine region 24 . Common and rare species represented 30.2% and 66.0% of species richness, respectively, but they accounted for only 40.1% and 11.2% of community biomassterm·key, respectively ( Supplementary Table 4 ). As a result, there was no significant relationship between community temporal stabilityterm·mth and common or rare species stability in our experimentterm·mth ( Supplementary Fig. 7 ). Overall, the significant positive relationship between dominant speciesterm·key stability and community biomassterm·key stability supports the mass ratio hypothesis 58 , highlighting the importance of dominant speciesterm·key for ecosystem functioning.

Our study provides new empirical evidence that climate warmingterm·dom can have a negative effect on the temporal stabilityterm·mth of community biomassterm·key production, independent of precipitationterm·key scenarios. This result suggests that future climate change may reduce the ability of our study system, the alpine grasslandterm·key that covers much of the Tibetan Plateauterm·key, to provide reliable ecosystem services for humanity. Future studies should assess the generality of this result to other ecosystems. Furthermore, our study identified weakened species asynchronyterm·dom as the main reason of why warmingterm·dom reduced the temporal stabilityterm·mth of community biomassterm·key. Elucidating how population dynamics of individual species respond to climate change in a community context thus holds the key to understanding changes in community stability properties under future climate scenarios.

Methods Study site Our study site is located at the Haibei Alpine Grasslandterm·key Ecosystem Research Station (101°12′E, 37°37′N, and 3,200 m above sea level) on the northeastern Tibetan Plateauterm·key in Qinghai Province, China. This area has a continental monsoon climate, with a 6-month growing season (from mid-April to mid-October). The mean annual temperature is −1.1 °C, with an extreme maximum air temperature of 27.6 °C in July, and an extreme minimum temperature of −37.1 °C in January. The mean annual precipitationterm·key is 485 mm, with >80% of the precipitationterm·key falling in the growing season. The soil is classified as Mat-Gryic Cambisol, with the average pH value of surface soil (0–10 cm) being 6.4 (refs 59 , 60 ). The alpine grasslandterm·key is dominated by perennial plants, including S. aliena , E. nutans , H. tibeticum , Kobresia capillifolia , Carex przewalskii , Poa annua , M. archiducis-nicolai , Tibetia ruthenia , Gentiana straminea and Saussurea superba . These species together account for ∼70% of aboveground net primary production (g m −2 ).

Experimental design Our experimental plots were established within an area of 50 m × 110 m in 2011, using a randomized block design with warmingterm·dom and altered precipitationterm·key as main treatment factors ( Supplementary Fig. 1a ). Each block contained six treatments, crossing two levels of warmingterm·dom (no warmingterm·dom, warmingterm·dom) and three levels of precipitationterm·key (no precipitationterm·key, drought (50% precipitationterm·key reduction) and wet (50% precipitationterm·key addition)). Each treatment had five replicates, resulting in 30 plots; each plot was 1.8 m × 2.2 m. In the warmingterm·dom treatments, two infrared heaters (1,000 mm length, 22 mm width) were suspended in parallel at 150 cm above the ground within each plot ( Supplementary Fig. 1b ), with an electrical power output of 1,200 W for each heater; the heaters resulted in an increase of 2 °C above ambient temperature at the top 5 cm layer of the soil 61 . Rain shelters were used to control the incoming precipitationterm·key amount in the experimental plots. Four ‘V'-shaped transparent polycarbonate resin channels (Teijin Chemical, Japan) were fixed at the 15° angle, above the infrared heaters, to intercept rainfall. The collected rainfall from the drought plots was supplied to the wet plots manually after each precipitationterm·key event by spraying bottle ( Supplementary Fig. 1c ). To account for the effects of shading, we also installed two ‘dummy' infrared heaters and four ‘dummy' transparent polycarbonate resin channels in the control plots. Stainless steel sheets were inserted into the soil around the edge of each plot to reduce surface runoff.

Plant community monitoring To estimate the biomassterm·key of community and individual species, three 0.15 m × 0.15 m quadrats were randomly chosen within each plot, and clipped at the ground level in late August (the peak of growing season) from 2011 to 2015. Plants clipped from the three quadrats of each plot were pooled together, sorted to species (from 2012 to 2015), and oven-dried at 65 °C for 48 h. Plants were classified into three different groups (dominant, common and rare species) according to their relative abundance and four functional groups (grasses, sedges, legumes and forbs) based on their functional forms. Dominant speciesterm·key included those with relative abundance >5%, common species ranged from 1 to 5% in relative abundance and rare species were those with relative abundance <1% (refs 62 , 63 , 64 ). The three groups consisted of 2, 16 and 35 species, and accounted for 52.3%, 35.9% and 11.9% of community biomassterm·key, respectively.

Statistical analysis We quantified temporal stabilityterm·mth of community biomassterm·key as the ratio of mean biomassterm·key ( μ ) to its temporal s.d. ( σ ) in each plot over the 5 years of the experimentterm·mth (2011–2015), as in many other studies 6 65 ; the temporal stabilityterm·mth of individual species and functional groups were calculated using the same method over the four years when species-level data were available (2012 to 2015). Species richness in each plot was defined as the total number of species detected in the three quadrats. We also calculated Simpson's dominance index 66 based on species biomassterm·key data. The degree of species asynchronyterm·dom was quantified by the community-wide asynchrony index 15 , defined as: where ϕ x is species synchrony, σ 2 is the variance of community biomassterm·key and σ i is the s.d. of biomassterm·key of species i in a plot with S species. This index attains one when species fluctuations are perfectly asynchronized, and attains zero when species fluctuations are perfectly synchronized.

No significant temporal trend in community biomassterm·key was detected during the experimental period; thus, no detrending was conducted. Linear mixed-effects models were used to assess the effects of warmingterm·dom, precipitationterm·key, year and their interactions on community/functional group biomassterm·key, species richness and dominance, in which warmingterm·dom, precipitationterm·key and year were treated as fixed factors, and block was treated as a random factor. Linear mixed-effects models were also used to assess the effects of warmingterm·dom, precipitationterm·key and their interactions on community biomassterm·key temporal stabilityterm·mth, species asynchronyterm·dom, the stability of the three different abundance groups (dominant, common and rare species) and the stability of the four functional groups (grasses, sedges, legumes and forbs), in which warmingterm·dom and precipitationterm·key were treated as fixed factors, and block was treated as a random factor. The significance threshold was pre-established as α=0.05.

Simple linear regressions was used to assess how species asynchronyterm·dom, species richness, dominance, the stability of the three abundance groups and the stability of the four functional groups relate to community biomassterm·key temporal stabilityterm·mth. Linear regressions were also used to assess the relationship between species richness/dominance and species asynchronyterm·dom, and the relationship between species relative abundance and population-level stability. Common/rare species stability was natural log transformed to ensure normality. ANCOVA was used to test whether the slopes of the linear regressions differed significantly among the six treatments.

SEMterm·mth was used to explore the pathways of how warmingterm·dom and altered precipitationterm·key, through influencing factors considered in the linear regressions, affected community biomassterm·key stability. We first considered a full model that included all possible pathways ( Fig. 4 and Supplementary Table 3 ), and then sequentially eliminated nonsignificant pathways until we attained the final model ( Supplementary Fig. 5 ). We used χ 2 test, Akaike information criteria and the root mean square error of approximation to evaluate the fit of model.

All statistical analyses were conducted using R version 3.2.2 (R Foundation for Statistical Computing, Vienna, Austria, 2013), with the ‘nlme' package for linear mixed-effects models, the ‘vegan' package for calculating Simpson's dominance index, the ‘ggplot2' package for plotting all histograms and regression figures and the ‘lavaan' package for SEMterm·mth 67 .

Data availability The data sets generated during the current study are available from the corresponding authors on reasonable request.

Additional information How to cite this article: Ma, Z. et al . Climate warmingterm·dom reduces the temporal stabilityterm·mth of plant community biomassterm·key production. Nat. Commun. 8, 15378 doi: 10.1038/ncomms15378 (2017).

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Material Supplementary Figures and Supplementary Tables