Management options influence seasonal CO2 soil emissions in Mediterranean olive ecosystems

Field trials were conducted at traditional Mediterranean olive agro-ecosystems grown at two locations (Italy –IT, Greece –GR). Groves were managed for many years using sustainable (S, cover crops, compost application, mulching of pruning biomass) or conventional (C) practices (e.g., soil tillage, burning of pruning residuals). The IT grove was rainfed (RAIN) while the GR was irrigated (IRR). This study examined the seasonal variation of soil CO2 emission (Rs) to explore the effect of the management options (C, S) on Rs at both sites. The second aim was to test the hypothesis that the seasonal Rs is differentially modulated by soil temperature and moisture, namely that (i) soil moisture limits Rs when it is below the lower limit of the readily available water (RAWLLim) and (ii) soil temperature above a threshold (max_T) reduces Rs even if soil moisture is non limiting. On the whole-season basis, the mean Rs rate at the rainfed site was 2.17 ± 0.06 (SE) at CRAIN and 2.32 ± 0.06 μmol CO2 m−2 s–1 at SRAIN plot, while at the irrigated site Rs was about 3.64 ± 0.11 (CIRR) and 4.05 ± 0.15 μmol CO2 m−2 s–1 (SIRR). The seasonal oscillation of Rs was consistent across locations and partitionable in three periods according to DOY (Day of Year) interval: Phase I (DOY 20–103 –GR; 20–118 -IT), Phase II (DOY 141÷257, GR; 142–257, IT) and Phase III (DOY 291–357, GR; 286–350, -IT). Pooling all the Rs data across sites and managements, max_T was ∼ 20 °C discriminating a differential response of Rs when soil moisture was < or > RAWLLim. These differential modulations exerted by temperature and moisture were integrated into a conditional model developed with a repeated random subsampling cross-validation procedure to effectively (R2 = 0.84) predict Rs. This paper mechanistically describes the interaction of the environment (soil moisture and temperature) and the management options (S, C) under various moisture conditions on Rs and would support carbon flux accounting procedures (e.g., regulating ecosystem services) tailored to the estimation of sink/source capability of traditional olive agro-ecosystem within environmental-friendly agricultural domains

Quantitative identification of functional connectivity disturbances in neuropsychiatric lupus based on resting-state fMRI: a robust machine learning approach

Neuropsychiatric systemic lupus erythematosus (NPSLE) is an autoimmune entity comprised of heterogenous syndromes affecting both the peripheral and central nervous system. Research on the pathophysiological substrate of NPSLE manifestations, including functional neuroimaging studies, is extremely limited. The present study examined person-specific patterns of whole-brain functional connectivity in NPSLE patients (n = 44) and age-matched healthy control participants (n = 39). Static functional connectivity graphs were calculated comprised of connection strengths between 90 brain regions. These connections were subsequently filtered through rigorous surrogate analysis, a technique borrowed from physics, novel to neuroimaging. Next, global as well as nodal network metrics were estimated for each individual functional brain network and were input to a robust machine learning algorithm consisting of a random forest feature selection and nested cross-validation strategy. The proposed pipeline is data-driven in its entirety, and several tests were performed in order to ensure model robustness. The best-fitting model utilizing nodal graph metrics for 11 brain regions was associated with 73.5% accuracy (74.5% sensitivity and 73% specificity) in discriminating NPSLE from healthy individuals with adequate statistical power. Closer inspection of graph metric values suggested an increased role within the functional brain network in NSPLE (indicated by higher nodal degree, local efficiency, betweenness centrality, or eigenvalue efficiency) as compared to healthy controls for seven brain regions and a reduced role for four areas. These findings corroborate earlier work regarding hemodynamic disturbances in these brain regions in NPSLE. The validity of the results is further supported by significant associations of certain selected graph metrics with accumulated organ damage incurred by lupus, with visuomotor performance and mental flexibility scores obtained independently from NPSLE patients. View Full-Text Keywords: neuropsychiatric systemic lupus erythematosus; rs-fMRI; graph theory; functional connectivity; surrogate data; machine learning; visuomotor ability; mental flexibilit

The effect of self‐generated versus externally generated actions on timing, duration, and amplitude of blood oxygen level dependent response for visual feedback processing

It has been widely assumed that internal forward models use efference copies to create predictions about the sensory consequences of our own actions. While these predictions have frequently been associated with a reduced blood oxygen level dependent (BOLD) response in sensory cortices, the timing and duration of the hemodynamic response for the processing of video feedback of self-generated (active) versus externally generated (passive) movements is poorly understood. In the present study, we tested the hypothesis that predictive mechanisms for self-generated actions lead to early and shorter neural processing compared with externally generated movements. We investigated active and passive movements using a custom-made fMRI-compatible movement device. Visual video feedback of the active and passive movements was presented in real time or with variable delays. Participants had to judge whether the feedback was delayed. Timing and duration of BOLD impulse response was calculated using a first (temporal derivative [TD]) and second-order (dispersion derivative [DD]) Taylor approximation. Our reanalysis confirmed our previous finding of reduced BOLD response for active compared to passive movements. Moreover, we found positive effects of the TD and DD in the supplementary motor area, cerebellum, visual cortices, and subcortical structures, indicating earlier and shorter hemodynamic responses for active compared to passive movements. Furthermore, earlier activation in the putamen for active compared to passive conditions was associated with reduced delay detection performance. These findings indicate that efference copy-based predictive mechanisms enable earlier processing of action feedback, which might have reduced the ability to detect short delays between action and feedback

Tomato TILLING Technology: Development of a Reverse Genetics Tool for the Efficient Isolation of Mutants from Micro-Tom Mutant Libraries

To accelerate functional genomic research in tomato, we developed a Micro-Tom TILLING (Targeting Induced Local Lesions In Genomes) platform. DNA pools were constructed from 3,052 ethyl methanesulfonate (EMS) mutant lines treated with 0.5 or 1.0% EMS. The mutation frequency was calculated by screening 10 genes. The 0.5% EMS population had a mild mutation frequency of one mutation per 1,710 kb, whereas the 1.0% EMS population had a frequency of one mutation per 737 kb, a frequency suitable for producing an allelic series of mutations in the target genes. The overall mutation frequency was one mutation per 1,237 kb, which affected an average of three alleles per kilobase screened. To assess whether a Micro-Tom TILLING platform could be used for efficient mutant isolation, six ethylene receptor genes in tomato (SlETR1–SlETR6) were screened. Two allelic mutants of SlETR1 (Sletr1-1 and Sletr1-2) that resulted in reduced ethylene responses were identified, indicating that our Micro-Tom TILLING platform provides a powerful tool for the rapid detection of mutations in an EMS mutant library. This work provides a practical and publicly accessible tool for the study of fruit biology and for obtaining novel genetic material that can be used to improve important agronomic traits in tomato

Multitrophic Interaction in the Rhizosphere of Maize: Root Feeding of Western Corn Rootworm Larvae Alters the Microbial Community Composition

BACKGROUND: Larvae of the Western Corn Rootworm (WCR) feeding on maize roots cause heavy economical losses in the US and in Europe. New or adapted pest management strategies urgently require a better understanding of the multitrophic interaction in the rhizosphere. This study aimed to investigate the effect of WCR root feeding on the microbial communities colonizing the maize rhizosphere. METHODOLOGY/PRINCIPAL FINDINGS: In a greenhouse experiment, maize lines KWS13, KWS14, KWS15 and MON88017 were grown in three different soil types in presence and in absence of WCR larvae. Bacterial and fungal community structures were analyzed by denaturing gradient gel electrophoresis (DGGE) of the 16S rRNA gene and ITS fragments, PCR amplified from the total rhizosphere community DNA. DGGE bands with increased intensity were excised from the gel, cloned and sequenced in order to identify specific bacteria responding to WCR larval feeding. DGGE fingerprints showed that the soil type and the maize line influenced the fungal and bacterial communities inhabiting the maize rhizosphere. WCR larval feeding affected the rhiyosphere microbial populations in a soil type and maize line dependent manner. DGGE band sequencing revealed an increased abundance of Acinetobacter calcoaceticus in the rhizosphere of several maize lines in all soil types upon WCR larval feeding. CONCLUSION/SIGNIFICANCE: The effects of both rhizosphere and WCR larval feeding seemed to be stronger on bacterial communities than on fungi. Bacterial and fungal community shifts in response to larval feeding were most likely due to changes of root exudation patterns. The increased abundance of A. calcoaceticus suggested that phenolic compounds were released upon WCR wounding

Enhanced Botrytis cinerea resistance of Arabidopsis plants grown in compost may be explained by increased expression of defense-related genes, as revealed by microarray analysis

Composts are the products obtained after the aerobic degradation of different types of organic matter waste and can be used as substrates or substrate/soil amendments for plant cultivation. There is a small but increasing number of reports that suggest that foliar diseases may be reduced when using compost, rather than standard substrates, as growing medium. The purpose of this study was to examine the gene expression alteration produced by the compost to gain knowledge of the mechanisms involved in compost-induced systemic resistance. A compost from olive marc and olive tree leaves was able to induce resistance against Botrytis cinerea in Arabidopsis, unlike the standard substrate, perlite. Microarray analyses revealed that 178 genes were differently expressed, with a fold change cut-off of 1, of which 155 were up-regulated and 23 were down-regulated in compost-grown, as against perlite-grown plants. A functional enrichment study of up-regulated genes revealed that 38 Gene Ontology terms were significantly enriched. Response to stress, biotic stimulus, other organism, bacterium, fungus, chemical and abiotic stimulus, SA and ABA stimulus, oxidative stress, water, temperature and cold were significantly enriched, as were immune and defense responses, systemic acquired resistance, secondary metabolic process and oxireductase activity. Interestingly, PR1 expression, which was equally enhanced by growing the plants in compost and by B. cinerea inoculation, was further boosted in compost-grown pathogen-inoculated plants. Compost triggered a plant response that shares similarities with both systemic acquired resistance and ABA-dependent/independent abiotic stress responses

The effect of self-generated versus externally generated actions on timing, duration, and amplitude of blood oxygen level dependent response for visual feedback processing

It has been widely assumed that internal forward models use efference copies to cre-ate predictions about the sensory consequences of our own actions. While these pre-dictions have frequently been associated with a reduced blood oxygen leveldependent (BOLD) response in sensory cortices, the timing and duration of thehemodynamic response for the processing of video feedback of self-generated(active) versus externally generated (passive) movements is poorly understood. In thepresent study, we tested the hypothesis that predictive mechanisms for self-generated actions lead to early and shorter neural processing compared with exter-nally generated movements. We investigated active and passive movements using acustom-made fMRI-compatible movement device. Visual video feedback of theactive and passive movements was presented in real time or with variable delays.Participants had to judge whether the feedback was delayed. Timing and duration ofBOLD impulse response was calculated using a first (temporal derivative [TD]) andsecond-order (dispersion derivative [DD]) Taylor approximation. Our reanalysis con-firmed our previous finding of reduced BOLD response for active compared to pas-sive movements. Moreover, we found positive effects of the TD and DD in thesupplementary motor area, cerebellum, visual cortices, and subcortical structures,indicating earlier and shorter hemodynamic responses for active compared to passivemovements. Furthermore, earlier activation in the putamen for active compared topassive conditions was associated with reduced delay detection performance. Thesefindings indicate that efference copy-based predictive mechanisms enable earlierprocessing of action feedback, which might have reduced the ability to detect shortdelays between action and feedback