Understanding the links between plant diversity and soil communities is critical to disentangling the mechanisms by which plant communities modulate ecosystem function. Experimental plant communities ...varying in species richness, evenness, and density were established using a response surface design and soil community properties including bacterial and archaeal abundance, richness, and evenness were measured. The potential to perform a representative soil ecosystem function, oxidation of ammonium to nitrite, was measured via archaeal and bacterial amoA genes. Structural equation modeling was used to explore the direct and indirect effects of the plant community on soil diversity and potential function. Plant communities influenced archaea and bacteria via different pathways. Species richness and evenness had significant direct effects on soil microbial community structure, but the mechanisms driving these effects did not include either root biomass or the pools of carbon and nitrogen available to the soil microbial community. Species richness had direct positive effects on archaeal amoA prevalence, but only indirect impacts on bacterial communities through modulation of plant evenness. Increased plant evenness increased bacterial abundance which in turn increased bacterial amoA abundance. These results suggest that plant community evenness may have a strong impact on some aspects of soil ecosystem function. We show that a more even plant community increased bacterial abundance, which then increased the potential for bacterial nitrification. A more even plant community, also increased total dissolved nitrogen in the soil, which decreased the potential for archaeal nitrification. The role of plant evenness in structuring the soil community suggests mechanisms including complementarity in root exudate profiles or root foraging patterns.
Precipitation is a primary climatic determinant of grassland productivity, with many global change experiments manipulating precipitation. Here we examine the impacts of precipitation addition and ...reduction treatment intensity and duration on grassland above- (ANPP) and below- (BNPP) ground net primary productivity in a large-scale meta-analysis. We tested, 1) the double asymmetry model of sensitivity, specifically whether the sensitivity of productivity decreases with treatment intensity under increased precipitation and increases with treatment intensity under decreased precipitation, 2) whether the sensitivity of productivity to precipitation change decreases with treatment length, and 3) how the sensitivity of productivity changes with climate conditions. ANPP showed higher sensitivity than BNPP under increased precipitation but similar sensitivity to BNPP under decreased precipitation. The sensitivity of ANPP and BNPP decreased with increasing treatment intensity (e.g., percentage change in precipitation, ΔPPT) and leveled off in the long-term. With increased precipitation, the sensitivity of productivity decreased with increasing treatment length (e.g., experimental duration) and leveled off in the long-term, whereas the sensitivity increased with increasing treatment length under reduced precipitation. Furthermore, the sensitivity of productivity to precipitation change decreased with increasing mean annual precipitation and temperature. Finally, our meta-analysis shows that above- and belowground net primary productivity have asymmetric responses to precipitation change. Together these results highlight the complex mechanisms underlying the impacts of precipitation change, particularly the intensity and duration of such changes, on grassland productivity.
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•ANPP sensitivity to IP was higher than BNPP, but it was similar with BNPP to DP.•The sensitivity of ANPP and BNPP to precipitation change decreased with ΔPPT.•Sensitivity to IP leveled off with ED, but sensitivity to DP increased with ED.
Soil invertebrates are an integral part of Arctic ecosystems through their roles in the breakdown of litter, soil formation, and nutrient cycling. However, studies examining soil invertebrates in the ...Arctic are limited and our understanding of the abiotic and biotic drivers of these invertebrate communities remains understudied. We examined differences in soil invertebrate taxa (mites, collembolans, enchytraeids) among several undisturbed upland tundra heath sites in Nunavut Canada and identified the drivers (vegetation and substrate cover, soil nutrients and pH) of the soil invertebrate community across these sites. Soil invertebrate densities were similar to that of other Arctic studies. While invertebrate communities were relatively consistent between our sites, cover of rocks, woody litter, and the lichen Alectoria nigricans had significant, positive influences on the density of all invertebrates studied. Mites and collembolans were more closely associated with cover of lichens, whereas enchytraeids were more closely associated with woody litter and rocks. Our results suggest that anthropogenic (e.g., resource exploration and extraction) and/or natural (e.g., climate change) disturbances that result in changes to the vegetation community and woody litter inputs will likely impact soil invertebrates and the ecosystem services they provide.
Plants Integrate Information About Nutrients and Neighbors Cahill, James F. Jr; McNickle, Gordon G; Haag, Joshua J ...
Science (American Association for the Advancement of Science),
06/2010, Letnik:
328, Številka:
5986
Journal Article
Recenzirano
Animals regularly integrate information about the location of resources and the presence of competitors, altering their foraging behavior accordingly. We studied the annual plant Abutilon theophrasti ...to determine whether a plant can demonstrate a similarly complex response to two conditions: presence of a competitor and heterogeneous resource distributions. Individually grown plants fully explored the pot by using a broad and uniform rooting distribution regardless of soil resource distributions. Plants with competitors and uniform soil nutrient distributions exhibited pronounced reductions in rooting breadth and spatial soil segregation among the competing individuals. In contrast, plants with competitors and heterogeneous soil nutrient distributions reduced their root growth only modestly, indicating that plants integrate information about both neighbor and resource distributions in determining their root behavior.
Increased nitrogen (N) inputs and subsequent effects on soil microbial stoichiometry have strong influences on organic matter decomposition and nutrient cycling. The effects of N addition on soil ...microbial stoichiometry are well documented, but we know little about the mechanisms linking between N addition and soil microbial stoichiometry. We examined how the effects of N addition cascade through soil properties (pH, available N (AN), available phosphorus (AP), dissolved organic carbon (DOC), DOC/AN, AN/AP and DOC/AP ratios), plant community composition (grasses, sedges, forbs, and legumes), plant resource stoichiometry (community-level leaf and root C/N/P ratios), and the composition of main microbial groups (phospholipid fatty acids profile) to influence microbial stoichiometry using a 5-year N fertilization field experiment in a Tibetan alpine meadow. We found that N addition changed soil microbial C/N and N/P ratios, but not microbial C/P ratios, indicating plasticity in microbial stoichiometry to increasing N deposition. Moreover, the changes in microbial stoichiometry were driven by N not C and P concentrations. Structural equation modeling revealed that N addition predominantly controlled soil microbial C/N and N/P ratios through plant leaf and root stoichiometry, but not the composition of plant community and main microbial groups. Our findings suggest that N addition-induced changes in plant resource stoichiometry are the core drivers of soil microbial stoichiometry responses to N deposition.
Multiple factors linked through complex networks of interaction including fertilization, aboveground biomass, and litter control the diversity of plant communities. The challenge of explaining plant ...diversity is to determine not only how each individual mechanism directly influences diversity, but how those mechanisms indirectly influence diversity through interactions with other mechanisms. This approach is well established in the study of plant species richness, but surprisingly little effort has been dedicated toward understanding the controls of community evenness, despite the recognition that this aspect of diversity can influence a variety of critical ecosystem functions. Similarly, studies of diversity have predominantly focused on the influence of shoot, rather than root, biomass, despite the fact that the majority of plant biomass is belowground in many natural communities. In this study, I examine the roles of belowground biomass, live aboveground biomass, litter, and light availability in controlling the species richness and evenness of a rough fescue grassland community using structural equation modeling. Litter was the primary mechanism structuring grassland diversity, with both richness and evenness declining with increasing litter cover. There were few relationship between root biomass, shading, and diversity, and more importantly, no relationship between root biomass and diversity. The lack of relationship between root biomass and species richness and evenness suggests that, even though root competition in grasslands is intense, belowground interactions may not play an important role in structuring community diversity or composition.
The development of microbial networks is central to ecosystem functioning and is the hallmark of complex natural systems. Characterizing network development over time and across environmental ...gradients is hindered by the millions of potential interactions among community members, limiting interpretations of network evolution. We developed a feature selection approach using data winnowing that identifies the most ecologically influential microorganisms within a network undergoing change. Using a combination of graph theory, leave-one-out analysis, and statistical inference, complex microbial communities are winnowed to identify the core organisms responding to external gradients or functionality, and then network development is evaluated against these externalities. In a plant invasion case study, the winnowed microbial network became more influential as the plant invasion progressed as a result of direct plant-microbe links rather than the expected indirect plant-soil-microbe links. This represents the first use of structural equation modeling to predict microbial network evolution, which requires identification of keystone taxa and quantification of the ecological processes underpinning community structure and function patterns.
Bacteria provide ecosystem services (e.g., biogeochemical cycling) that regulate climate, purify water, and produce food and other commodities, yet their distribution and likely responses to change ...or intervention are difficult to predict. Using bacterial 16S rRNA gene surveys of 1,381 soil samples from the Biomes of Australian Soil Environment (BASE) dataset, we were able to model relative abundances of soil bacterial taxonomic groups and describe bacterial niche space and optima. Hold out sample validated hypothetical causal networks (structural equation models; SEM) were able to predict the relative abundances of bacterial taxa from environmental data and elucidate soil bacterial niche space. By using explanatory SEM properties as indicators of microbial traits, we successfully predicted soil bacterial response, and in turn potential ecosystem service response, to near-term expected changes in the Australian climate. The methods developed enable prediction of continental-scale changes in bacterial relative abundances, and demonstrate their utility in predicting changes in bacterial function and thereby ecosystem services. These capabilities will be strengthened in the future with growing genome-level data.
We evaluated above‐ and belowground ecosystem changes in a 16 year, combined fertilization and warming experiment in a High Arctic tundra deciduous shrub heath (Alexandra Fiord, Ellesmere Island, NU, ...Canada). Soil emissions of the three key greenhouse gases (GHGs) (carbon dioxide, methane, and nitrous oxide) were measured in mid‐July 2009 using soil respiration chambers attached to a FTIR system. Soil chemical and biochemical properties including Q10 values for CO2, CH4, and N2O, Bacteria and Archaea assemblage composition, and the diversity and prevalence of key nitrogen cycling genes including bacterial amoA, crenarchaeal amoA, and nosZ were measured. Warming and fertilization caused strong increases in plant community cover and height but had limited effects on GHG fluxes and no substantial effect on soil chemistry or biochemistry. Similarly, there was a surprising lack of directional shifts in the soil microbial community as a whole or any change at all in microbial functional groups associated with CH4 consumption or N2O cycling in any treatment. Thus, it appears that while warming and increased nutrient availability have strongly affected the plant community over the last 16 years, the belowground ecosystem has not yet responded. This resistance of the soil ecosystem has resulted in limited changes in GHG fluxes in response to the experimental treatments.
Modifying the rhizosphere microbiome through targeted plant breeding is key to harnessing positive plant-microbial interrelationships in cropping agroecosystems. Here, we examine the composition of ...rhizosphere bacterial communities of diverse
genotypes to identify: (1) taxa that preferentially associate with genotypes, (2) core bacterial microbiota associated with
, (3) heritable alpha diversity measures at flowering and whole growing season, and (4) correlation between microbial and plant genetic distance among canola genotypes at different growth stages. Our aim is to identify and describe signature microbiota with potential positive benefits that could be integrated in
breeding and management strategies. Rhizosphere soils of 16 diverse genotypes sampled weekly over a 10-week period at single location as well as at three time points at two additional locations were analyzed using 16S rRNA gene amplicon sequencing. The
rhizosphere microbiome was characterized by diverse bacterial communities with 32 named bacterial phyla. The most abundant phyla were Proteobacteria, Actinobacteria, and Acidobacteria. Overall microbial and plant genetic distances were highly correlated (
= 0.65). Alpha diversity heritability estimates were between 0.16 and 0.41 when evaluated across growth stage and between 0.24 and 0.59 at flowering. Compared with a reference
genotype, a total of 81 genera were significantly more abundant and 71 were significantly less abundant in at least one
genotype out of the total 558 bacterial genera. Most differentially abundant genera were Proteobacteria and Actinobacteria followed by Bacteroidetes and Firmicutes. Here, we also show that
genotypes select an overall core bacterial microbiome with growth-stage-related patterns as to how taxa joined the core membership. In addition, we report that sets of
core taxa were consistent across our three sites and 2 years. Both differential abundance and core analysis implicate numerous bacteria that have been reported to have beneficial effects on plant growth including disease suppression, antifungal properties, and plant growth promotion. Using a multi-site year, temporally intensive field sampling approach, we showed that small plant genetic differences cause predictable changes in canola microbiome and are potential target for direct and indirect selection within breeding programs.
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