Isotopic Analysis of Sporocarp Protein and Structural Material Improves Resolution of Fungal Carbon Sources

Fungal acquisition of resources is difficult to assess in the field. To determine whether fungi received carbon from recent plant photosynthate, litter or soil-derived organic (C:N bonded) nitrogen, we examined differences in δ13C among bulk tissue, structural carbon, and protein extracts of sporocarps of three fungal types: saprotrophic fungi, fungi with hydrophobic ectomycorrhizae, or fungi with hydrophilic ectomycorrhizae. Sporocarps were collected from experimental plots of the Duke Free-air CO2 enrichment experiment during and after CO2 enrichment. The differential 13C labeling of ecosystem pools in CO2 enrichment experiments was tracked into fungi and provided novel insights into organic nitrogen use. Specifically, sporocarp δ13C as well as δ15N of protein and structural material indicated that fungi with hydrophobic ectomycorrhizae used soil-derived organic nitrogen sources for protein carbon, fungi with hydrophilic ectomycorrhizae used recent plant photosynthates for protein carbon and both fungal groups used photosynthates for structural carbon. Saprotrophic fungi depended on litter produced during fumigation for both protein and structural material

Isotopic Analysis of Sporocarp Protein and Structural Material Improves Resolution of Fungal Carbon Sources

Fungal acquisition of resources is difficult to assess in the field. To determine whether fungi received carbon from recent plant photosynthate, litter or soil-derived organic (C:N bonded) nitrogen, we examined differences in δ13C among bulk tissue, structural carbon, and protein extracts of sporocarps of three fungal types: saprotrophic fungi, fungi with hydrophobic ectomycorrhizae, or fungi with hydrophilic ectomycorrhizae. Sporocarps were collected from experimental plots of the Duke Free-air CO2 enrichment experiment during and after CO2 enrichment. The differential 13C labeling of ecosystem pools in CO2 enrichment experiments was tracked into fungi and provided novel insights into organic nitrogen use. Specifically, sporocarp δ13C as well as δ15N of protein and structural material indicated that fungi with hydrophobic ectomycorrhizae used soil-derived organic nitrogen sources for protein carbon, fungi with hydrophilic ectomycorrhizae used recent plant photosynthates for protein carbon and both fungal groups used photosynthates for structural carbon. Saprotrophic fungi depended on litter produced during fumigation for both protein and structural material

Microcredit in the Rural Areas of Northwest Yunnan Province, China: Investigating the Operation of, Results of, and Obstacles to Microfinancial Institutions

The UN declared 2005 the Silver Year of International Microfinance, due to the successes of microcredit programs in underdeveloped countries around the world since the phenomenon first started appearing in the eighties and nineties. Although programs succeed, it is not without great effort, extended time periods, and competent administration. Previous research of microfinance in Yunnan Province, China has indicated that some of the greatest barriers to success in the programs are their administrative costs and instability, information inequity, and borrowers’ misunderstanding of policies or refusal to adhere to those policies. The purpose of this paper will be to investigate in what ways microfinancial institutions are dealing with or could be dealing with these sorts of problems, and also to evaluate the efficacy of microcredit in Lijiang County for alleviating poverty and generating increases in income

Understanding microbial contributions to soil aggregation and organic matter accumulation

The goal of the project investigators was to characterize soil bacterial and fungal communities and the rates at which they break down specific plant-derived carbon (C) molecules within soil aggregates in three farming systems

Anomalieerkennung in Kommunikationsdaten zur Datenselektion im Fahrzeug

Ein Fahrzeug generiert Daten, welche Zustand und Verhalten von Fahrer und Fahrzeug beschreiben. Das Sammeln der Informationen gibt dem Automobilhersteller die Möglichkeit, diese als Big Data zu verwenden und neuen Wert zu schöpfen. Beispielsweise schafft die Beobachtung während des gesamten Lebenszyklus die Grundlage für eine Produktoptimierung, oder aber das Marketing kann zielgerichtet auf die individuellen Wünsche des Kunden eingehen. Herausforderungen hierbei liegen darin, einen Wert aus den Daten zu schöpfen und die Übertragung von Fahrzeug zu Backend reduzieren. Ein Oberklassefahrzeug generiert im Jahr 2017 2,1 MByte je Sekunde. Für die Übertragung der Datenmenge, die eine Flotte mit Millionen von Fahrzeugen erzeugt, ergeben sich daher Schwierigkeiten. Aufgrund der Übertragungskosten, der Datenschutzgrundverordnung und der Limitierung in der Datenübertragung ist bereits im Fahrzeug eine Selektion relevanter Informationen notwendig. Der Ansatz der one-class Klassifizierung lernt anhand normaler Flottendaten, was normal ist und kann somit Abweichungen vom Normalzustand erkennen. Durch die Übertragung des trainierten Modells in die Fahrzeuge werden dort unmittelbar anormale Ereignisse erkannt, womit der Datentransfer zum Backend auf das Wesentliche, die außergewöhnlichen Vorkommnisse, reduziert wird. Durch eine stetige Aktualisierung des Modells entsteht eine dynamische Datensammlung, welche sicherstellt, dass im Backend noch fehlende Ereignisse übermittelt werden. Der Vergleich unterschiedlicher Ansätze verdeutlicht, dass insbesondere das Replikator Neuronale Netz die Anforderungen erfüllt. Außerdem ist es in der Lage, einen Großteil real geschehener Anomalien zu erkennen, während kein normales Event fälschlicherweise als anormal eingestuft wird. Das Ziel der Datenreduktion um das Hundertfache führt zur tatsächlichen Einschränkung auf 0,715%. Die bedeutsamsten Ereignisse, wie Unfälle oder ABS-Eingriffe, sind klar erkennbar, doch eine durchschnittliche Area under curve von 0,8 legt dar, dass das Vorgehen kein Alarmsystem liefert. Es dient der Reduktion der Datenmenge, die ins Backend übertragen wird, wo weiteres Postprocessing erfolgen muss. Dieses besteht aus der Interpretation und der Einordnung von erkannten Ereignissen

Long-term carbon and nitrogen dynamics at SPRUCE revealed through stable isotopes in peat profiles

Peatlands encode information about past vegetation dynamics, climate, and microbial processes. Here, we used δ15N and δ13C patterns from 16 peat profiles to deduce how the biogeochemistry of the Marcell S1 forested bog in northern Minnesota responded to environmental and vegetation change over the past  ∼ 10000 years. In multiple regression analyses, δ15N and δ13C correlated strongly with depth, plot location, C∕N, %N, and each other. Correlations with %N, %C, C∕N, and the other isotope accounted for 80% of variance for δ15N and 38% of variance for δ13C, reflecting N and C losses. In contrast, correlations with depth and topography (hummock or hollow) reflected peatland successional history and climate. Higher δ15N in plots closer to uplands may reflect upland-derived DON inputs and accompanying shifts in N dynamics in the lagg drainage area surrounding the bog. The Suess effect (declining δ13CO2 since the Industrial Revolution) lowered δ13C in recent surficial samples. High δ15N from −35 to −55cm probably indicated the depth of ectomycorrhizal activity after tree colonization of the peatland over the last 400 years, as confirmed by the occasional presence of wood down to −35cm depth. High δ13C at  ∼ 4000 years BP (−65 to −105cm) could reflect a transition at that time to slower rates of peat accumulation, when 13C discrimination during peat decomposition may increase in importance. Low δ13C and high δ15N at −213 and −225cm ( ∼ 8500 years BP) corresponded to a warm period during a sedge-dominated rich fen stage. The above processes appear to be the primary drivers of the observed isotopic patterns, whereas there was no clear evidence for methane dynamics influencing δ13C patterns

Effects of elevated atmospheric carbon dioxide on amino acid and NH 4 + -N cycling in a temperate pine ecosystem

Rising atmospheric carbon dioxide (CO 2 ) is expected to increase forest productivity, resulting in greater carbon (C) storage in forest ecosystems. Because elevated atmospheric CO 2 does not increase nitrogen (N) use efficiency in many forest tree species, additional N inputs will be required to sustain increased net primary productivity (NPP) under elevated atmospheric CO 2 . We investigated the importance of free amino acids (AAs) as a source for forest N uptake at the Duke Forest Free Air CO 2 Enrichment (FACE) site, comparing its importance with that of better-studied inorganic N sources. Potential proteolytic enzyme activity was monitored seasonally, and individual AA concentrations were measured in organic horizon extracts. Potential free AA production in soils ranged from 190 to 690 nmol N g −1  h −1 and was greater than potential rates of soil NH 4 + production. Because of this high potential rate of organic N production, we determined (1) whether intact AA uptake occurs by Pinus taeda L., the dominant tree species at the FACE site, (2) if the rate of cycling of AAs is comparable with that of ammonium (NH 4 + ), and (3) if atmospheric CO 2 concentration alters the aforementioned N cycling processes. A field experiment using universally labeled ammonium ( 15 NH 4 + ) and alanine ( 13 C 3 H 7 15 NO 2 ) demonstrated that 15 N is more readily taken up by plants and heterotrophic microorganisms as NH 4 + . Pine roots and microbes take up on average 2.4 and two times as much NH 4 + 15 N compared with alanine 15 N 1 week after tracer application. N cycling through soil pools was similar for alanine and NH 4 + , with the greatest 15 N tracer recovery in soil organic matter, followed by microbial biomass, dissolved organic N, extractable NH 4 + , and fine roots. Stoichiometric analyses of 13 C and 15 N uptake demonstrated that both plants and soil microorganisms take up alanine directly, with a 13 C :  15 N ratio of 3.3 : 1 in fine roots and 1.5 : 1 in microbial biomass. Our results suggest that intact AA (alanine) uptake contributes substantially to plant N uptake in loblolly pine forests. However, we found no evidence supporting increased recovery of free AAs in fine roots under elevated CO 2 , suggesting plants will need to acquire additional N via other mechanisms, such as increased root exploration or increased N use efficiency.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73167/1/j.1365-2486.2007.01411.x.pd

Species composition but not diversity explains recovery from the 2011 drought in Texas grasslands

Extreme droughts can have profound direct consequences for grassland ecosystems, but it is poorly known how ecosystems recover from drought and what ecological factors are associated with recovery. Recovery occurs when ecosystem functioning returns to values observed prior to a perturbation. Here, we tested for ecosystem recovery after an extreme drought in 2011 in previously established native and exotic experimental communities in Central Texas. Planted mixtures of all native and all exotic species were crossed with a summer irrigation treatment, with eight community compositions (random draws) per treatment. Prior to the drought, native plots had higher diversity than exotic plots, which sets up the prediction that the high-diversity native plots will recover more quickly than exotics. The extreme drought decreased rain-use efficiency ([RUE], annual biomass production per unit of rainfall) by 82%. Rain-use efficiency remained well below pre-drought levels during the growing season after the drought. However, on average, RUE recovered to pre-drought levels by the second growing season following drought. Exotic communities showed higher RUE than native communities, and irrigation significantly reduced RUE in both exotic and native communities across years. Interestingly, not all of the mixtures recovered from the drought, and recovery was associated with species composition, but not diversity. Rain-use efficiency recovery from drought was greatest in native communities in which the proportion of C3 forb biomass increased during and following drought and in exotic communities with a low proportion of short grass biomass. Extreme droughts can exert differential impacts on plant functional groups, leading to a drought legacy effect that reduces recovery with possible long-term repercussions