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opencc-zeroDec 2014View details →

Data from: Indirect effects of global change accumulate to alter plant diversity but not ecosystem function in alpine tundra

1. Environmental change can affect species directly by altering their physical environment and indirectly by altering the abundance of interacting species. A key challenge at the interface of community ecology and conservation biology is to predict how direct and indirect effects combine to influence response in a changing environment. In particular, little is known about how direct and indirect effects on biodiversity develop over time or their potential to influence ecosystem function. 2. We studied how nitrogen (N), winter precipitation (snow), and warming influenced diversity and ecosystem function over six years in alpine tundra. We used path analyses to partition direct effects of environmental manipulations from indirect effects due to changes in the abundance of two dominant plants. We hypothesize that 1) indirect effects will develop more slowly but will become stronger than direct effects over time, and 2) after six years, indirect effects will more strongly influence diversity while direct effects will influence ecosystem function. 3. Indirect effects of N on diversity were consistently stronger than direct effects and actually developed quickly, prior to direct effects. Direct effects of snow on diversity were detected in year two but then subsequently were reversed, while indirect effects were detected in year four and grew stronger over time. Overall in year six, indirect effects were much stronger than direct effects. 4. Direct effects predominated for three of four ecosystem functions we measured (productivity, N mineralization, winter N availability). The only indirect effects we found were that N and snow indirectly affected microbial biomass N by influencing Geum abundance. Across all four ecosystem measures, indirect effects were infrequent and weaker than direct effects. 5. Synthesis. Increasing indirect effects on diversity over time indicate that short-term experiments or monitoring of natural systems may underestimate the full magnitude of global change effects on plant communities. Explicitly accounting for changes in dominant plant abundance may be necessary for forecasting plant community response to environmental change. Conversely, weak indirect effects for ecosystem processes suggest that predicting ecosystem function without knowledge of plant responses to global change may be possible.

opencc-zeroDec 2021View details →

Disentangling the roles of plant functional diversity and plaint traits in regulating plant nitrogen accumulation and denitrification in freshwaters

1. There is a growing recognition that functional measures of diversity, based on quantification of functionally important species traits, are useful for explaining variation in ecosystem processes. However, the mechanisms linking functional diversity to different processes remain poorly understood, hindering development of a predictive framework for ecosystem functioning based on species traits. 2. The current understanding of how the functional traits of aquatic plants (macrophytes) affect nitrogen (N) cycling by regulating microbial communities and their activity in freshwater habitats is particularly limited. Denitrifying bacteria are typically associated with the roots of both aquatic and terrestrial plants and denitrification is the main cause of loss of N from ecosystems. Disentangling the interplay between plants and microbial denitrifiers is key to understanding variation in rates of denitrification from local to landscape scales. 3. In a mesocosm experiment, we varied the species richness (monocultures or two- species mixtures) and composition of macrophytes. We quantified effects of both macrophyte functional diversity, quantified as functional trait dissimilarity, and functional trait composition, quantified as community weighted mean trait values, on N removal in wetlands. We used structural equation modelling to disentangle the direct and indirect influences of traits on N accumulation in plant biomass, denitrification activity and abundance of key bacterial denitrification genes (nirSand nirK). 4. Both functional diversity and functional trait composition regulated N removal, explaining 70 – 94% variation in the underlying ecosystem processes. Increased macrophyte functional diversity increased plant N accumulation, and indirectly enhanced denitrification by increasing denitrification gene abundance. Among traits, greater plant relative growth rates, specific leaf area and aboveground biomass increased plant N accumulation. Denitrification activity increased with increasing belowground biomass but decreased with increasing root diameter. 5. These findings improve our understanding of N removal in freshwater wetlands dominated by macrophytes, and have broad ecological implications for wetland management targeting enhanced ecosystem services. Our results highlight the potential for optimising denitrification and plant N accumulation in wetlands and thereby improving water purification by increasing macrophyte functional diversity and ensuring the presence of key traits in macrophyte assemblages.

opencc-zeroMar 2023View details →

Climate warming alters the relative importance of plant root and microbial community in regulating the accumulation of soil microbial necromass carbon in a Tibetan alpine meadow

Climate warming is predicted to considerably affect variations in soil organic carbon (SOC), especially in alpine ecosystems. Microbial necromass carbon (MNC) is an important contributor to stable soil organic carbon pools. However, accumulation and persistence of soil MNC across a gradient of warming are still poorly understood. An eight-year field experiment with four levels of warming was conducted in a Tibetan meadow. We found that low-level (+0-1.5 ℃) warming mostly enhanced bacterial necromass carbon (BNC), fungal necromass carbon (FNC), and total MNC compared with control treatment across soil layers, while no significant effect was caused between high-level (+1.5-2.5 ℃) treatments and control treatments. The contributions of both MNC and BNC to soil organic carbon were not significantly affected by warming treatments across depths. Structural equation modeling analysis demonstrated that the effect of plant root traits on MNC persistence strengthened with warming intensity, while the influence of microbial community characteristics waned along with strengthened warming. Overall, our study provides novel evidence that the major determinants of MNC production and stabilization may vary with warming magnitude in alpine meadows. This finding is critical for updating our knowledge of soil carbon storage in response to climate warming.

opennotspecifiedFeb 2023View details →

Fig. 1 in Isoavenaciol and 7-hydroxy-isoavenaciol: Zn-chelating metallophores produced by root-endophytic Pezicula ericae in a Zn-accumulating plant, Aucuba japonica

Fig. 1. Zn-chelating activity of each sample solution. The activities were shown as means ± standard errors (n = 3). (+) indicates that a clear zone only inside the steel cup or paper disk. The different letters indicate a statistically significant difference was observed in one-way ANOVA and post-hoc Scheffe´at P <0.05.

Fig. 7 in Sites of biosynthesis and storage of Taxol in Taxus media (Rehder) plants: Mechanism of accumulation

Fig. 7. Model summarizes the dynamic production of Taxol in Taxus plant stem sections suggesting wood as the site of Taxol biosynthesis, and phloem and outer bark as the sites of storage.

Fig. 6 in Sites of biosynthesis and storage of Taxol in Taxus media (Rehder) plants: Mechanism of accumulation

Fig. 6. In situ immuno-labelling of TS enzyme and Taxol in Taxus stem transverse sections. (A) Control stem section received no primary Abs compared to (B) a section that received anti-TS Ab and (C) a section that received anti-Taxol Ab.

Fig. 5 in Sites of biosynthesis and storage of Taxol in Taxus media (Rehder) plants: Mechanism of accumulation

Fig. 5. Comparison between Taxus plant (A-G) tissues, (H–N) organs and (O–W) age on the contents of (A, H, O) Taxol (B, I, P) baccatin III, (C, J, Q) polyphenols, (D, K, R) HB and the expression of (E, L, S) TS, (F, M, T) PAL and (G, N, W) PAM genes. In case of (D) the comparison was between wood and phloem only, since the bark did not show HB. The data are displayed as the mean ± standard error of the mean. The statistical significance was calculated with a Student-T-test and oneway ANOVA, and the significance level indicated by asterisks. P-value <0.05 was considered significant.

Fig. 4 in Sites of biosynthesis and storage of Taxol in Taxus media (Rehder) plants: Mechanism of accumulation

Fig. 4. Comparison between intact plant and plant callus culture (TC) in terms of (A) taxoid contents (Taxol versus baccatin III), number of HB (indicated as red droplets) in (B) TC and (C) intact plant stem sections, and expression of (D and E) TS, (F) PAL and (G) PAM genes. The data are displayed as the mean ± standard error of the mean. The statistical significance was calculated with the Student-t-test and the significance level indicated by asterisks. P-value <0.05 was considered significant. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 2 in Sites of biosynthesis and storage of Taxol in Taxus media (Rehder) plants: Mechanism of accumulation

Fig. 2. Taxol localization and storage. (A) Transverse section of a Taxus plant stem showing the location of Taxol-containing HB (red-stained droplets) within the wood and phloem in comparison to (B) close up view in the vascular bundle (VB) of a root section and (C) close up view in the vascular bundle (VB) of a needle (Taxus leaf) section. (D) and (E) Close up views in the wood and phloem, respectively, to show the distribution of Taxol-containing HB within Taxus stem sections. (F) Pearson's correlation between Taxol content and the number of HB within different plant samples (Pearson's correlation, r2 = 0.77). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3 in Sites of biosynthesis and storage of Taxol in Taxus media (Rehder) plants: Mechanism of accumulation

Fig. 3. Correlation of Taxol accumulation to (A) baccatin III accumulation (Pearson's correlation, r2 = 0.12), (B) polyphenol accumulation (Pearson's correlation, r2 = 0.95) and (C) TS gene expression (Pearson's correlation, r2 = 0.07). (D) Correlation of baccatin III to TS gene expression (Pearson's correlation, r2 = 0.80). The data were analyzed using Pearson's correlation and the data were considered to have a normal distribution. P value <0.05 was considered as significant.