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Summary: Rising atmospheric carbon dioxide concentrations (CO2) and atmospheric nitrogen (N) deposition have contrasting effects on ectomycorrhizal (EM) and arbuscular mycorrhizal (AM) symbioses, potentially mediating forest responses to environmental change.In this study, we evaluated the cumulative effects of historical environmental change on N concentrations and δ15N values in AM plants, EM plants, EM fungi, and saprotrophic fungi using herbarium specimens collected in Minnesota, USA from 1871 to 2016. To better understand mycorrhizal mediation of foliar δ15N, we also analyzed a subset of previously published foliar δ15N values from across the United States to parse the effects of N deposition and CO2 rise.Over the last century in Minnesota, N concentrations declined among all groups except saprotrophic fungi. δ15N also declined among all groups of plants and fungi; however, foliar δ15N declined less in EM plants than in AM plants. In the analysis of previously published foliar δ15N values, this slope difference between EM and AM plants was better explained by nitrogen deposition than by CO2 rise.Mycorrhizal type did not explain trajectories of plant N concentrations. Instead, plants and EM fungi exhibited similar declines in N concentrations, consistent with declining forest N status despite moderate levels of N deposition. [ABSTRACT FROM AUTHOR]

Intermediate wheatgrass (Thinopyrum intermedium; IWG) is a perennial grass under development as a grain and forage crop. Although IWG is known for its ability to take up nitrate and improve water quality, seasonal nitrogen (N) demand and uptake by IWG is not well known. We measured IWG shoot, root, and grain production, tissue N concentration, and soil mineral N at multiple plant growth stages in 1- and 2-year-old IWG stands fertilized with various rates of N: (1) 80 kg N ha−1 applied at spring regrowth (spring), (2) 40–40 kg N ha−1 applied at spring regrowth and anthesis (split), and (3) an unfertilized control. We also calculated nitrogen use efficiency and biomass N yield. Soil mineral N, N-mineralization rates, and plant N concentration increased with fertilization, and lodging increased with spring fertilization, while root physiological N use efficiency (PNUE) declined with fertilization. Seasonally, shoot and root N concentration declined at physiological maturity, while shoot PNUE was highest at maturity, suggesting either that surplus N was allocated to grain or that more biomass was being produced per unit N taken up. In the 1-year-old stand, during fall regrowth, soil mineral N levels were among the lowest; however, the total soil N was highest compared with other sampling times, suggesting a large influx of organic N between physiological maturity and fall regrowth. Based on our results, IWG is well suited to use nitrogen inputs and avoid excess N leaching into groundwater, but it is also clear that IWG has strong seasonal N allocation patterns that should be taken into consideration with N recommendations and best practices. [ABSTRACT FROM AUTHOR]

Soil microbial communities play a critical role in nutrient transformation and storage in all ecosystems. Quantifying the seasonal and long-term temporal extent of genetic and functional variation of soil microorganisms in response to biotic and abiotic changes within and across ecosystems will inform our understanding of the effect of climate change on these processes. We examined spatial and seasonal variation in microbial communities based on 16S rRNA gene sequencing and phospholipid fatty acid (PLFA) composition across four biomes: a tropical broadleaf forest (Hawaii), taiga (Alaska), semiarid grassland-shrubland (Utah), and a subtropical coniferous forest (Florida). In this study, we used a team-based instructional approach leveraging the iPlant Collaborative to examine publicly available National Ecological Observatory Network (NEON) 16S gene and PLFA measurements that quantify microbial diversity, composition, and growth. Both profiling techniques revealed that microbial communities grouped strongly by ecosystem and were predominately influenced by three edaphic factors: pH, soil water content, and cation exchange capacity. Temporal variability of microbial communities differed by profiling technique; 16S-based community measurements showed significant temporal variability only in the subtropical coniferous forest communities, specifically through changes within subgroups of Acidobacteria. Conversely, PLFA-based community measurements showed seasonal shifts in taiga and tropical broadleaf forest systems. These differences may be due to the premise that 16S-based measurements are predominantly influenced by large shifts in the abiotic soil environment, while PLFA-based analyses reflect the metabolically active fraction of the microbial community, which is more sensitive to local disturbances and biotic interactions. To address the technical issue of the response of soil microbial communities to sample storage temperature, we compared 16S-based community structure in soils stored at -80°C and -20°C and found no significant differences in community composition based on storage temperature. Free, open access datasets and data sharing platforms are powerful tools for integrating research and teaching in undergraduate and graduate student classrooms. They are a valuable resource for fostering interdisciplinary collaborations, testing ecological theory, model development and validation, and generating novel hypotheses. Training in data analysis and interpretation of large datasets in university classrooms through project-based learning improves the learning experience for students and enables their use of these significant resources throughout their careers. [ABSTRACT FROM AUTHOR]

The widespread paradigm in ecology that community structure determines function has recently been challenged by the high complexity of microbial communities. Here, we investigate the patterns of and connections between microbial community structure and microbially-mediated ecological function across different forest management practices and temporal changes in leaf litter across beech forest ecosystems in Central Europe. Our results clearly indicate distinct pattern of microbial community structure in response to forest management and time. However, those patterns were not reflected when potential enzymatic activities of microbes were measured. We postulate that in our forest ecosystems, a disconnect between microbial community structure and function may be present due to differences between the drivers of microbial growth and those of microbial function. [ABSTRACT FROM AUTHOR]

Biodiversity-ecosystem functioning ( BEF) experiments address ecosystem-level consequences of species loss by comparing communities of high species richness with communities from which species have been gradually eliminated. BEF experiments originally started with microcosms in the laboratory and with grassland ecosystems. A new frontier in experimental BEF research is manipulating tree diversity in forest ecosystems, compelling researchers to think big and comprehensively., We present and discuss some of the major issues to be considered in the design of BEF experiments with trees and illustrate these with a new forest biodiversity experiment established in subtropical China ( Xingangshan, Jiangxi Province) in 2009/2010. Using a pool of 40 tree species, extinction scenarios were simulated with tree richness levels of 1, 2, 4, 8 and 16 species on a total of 566 plots of 25·8 × 25·8 m each., The goal of this experiment is to estimate effects of tree and shrub species richness on carbon storage and soil erosion; therefore, the experiment was established on sloped terrain. The following important design choices were made: (i) establishing many small rather than fewer larger plots, (ii) using high planting density and random mixing of species rather than lower planting density and patchwise mixing of species, (iii) establishing a map of the initial 'ecoscape' to characterize site heterogeneity before the onset of biodiversity effects and (iv) manipulating tree species richness not only in random but also in trait-oriented extinction scenarios., Data management and analysis are particularly challenging in BEF experiments with their hierarchical designs nesting individuals within-species populations within plots within-species compositions. Statistical analysis best proceeds by partitioning these random terms into fixed-term contrasts, for example, species composition into contrasts for species richness and the presence of particular functional groups, which can then be tested against the remaining random variation among compositions., We conclude that forest BEF experiments provide exciting and timely research options. They especially require careful thinking to allow multiple disciplines to measure and analyse data jointly and effectively. Achieving specific research goals and synergy with previous experiments involves trade-offs between different designs and requires manifold design decisions. [ABSTRACT FROM AUTHOR]