scholarly journals The structure of plant spatial association networks increases plant diversity in global drylands

2017 ◽  
Author(s):  
H. Saiz ◽  
J. Gómez-Gardeñes ◽  
J.P. Borda ◽  
F.T. Maestre
Keyword(s):  
Plant Communities ◽  
Plant Diversity ◽  
Network Structure ◽  
Structural Equation Models ◽  
Abiotic Factors ◽  
Complex Structure ◽  
Spatial Association ◽  
System Level ◽  
Soil Conditions ◽  
Network Analyses

AbstractAimDespite their widespread use and value to unveil the complex structure of the interactions within ecological communities and their value to assess the resilience of communities, network analyses have seldom been applied in plant communities. We aim to evaluate how plant-plant interaction networks vary in global drylands, and to assess whether network structure is related to plant diversity in these ecosystems.Location185 dryland ecosystems from all continents except Antarctica.MethodsWe built networks using the local spatial association between all the perennial plant species present in the communities studied, and used structural equation models to evaluate the effect of abiotic factors (including geography, topography, climate and soil conditions) and network structure on plant diversity.ResultsThe structure of plant networks found at most study sites (72%) was not random and presented properties representative of robust systems, such as high link density and structural balance. Moreover, network indices linked to system robustness had a positive and significant effect on plant diversity, sometimes higher that the effect of abiotic factors.Main conclusionsOur results constitute the first empirical evidence showing the existence of a common network architecture structuring terrestrial plant communities at the global scale, and provide novel evidence of the importance of the network of interactions for the maintenance of biodiversity. Furthermore, they highlight the importance of system-level approaches to explain the diversity and structure of interactions in plant communities, two major drivers of terrestrial ecosystem functioning and resilience against the likely impacts derived from global change.

scholarly journals AB0080 A SYSTEM-LEVEL APPROACH IDENTIFIES A CRITICAL REGULATOR OF CHONDROSARCOMA PROGRESSION

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1340.3-1340
Author(s):  
H. Kim ◽  
Y. Cho ◽  
J. H. Kim
Keyword(s):  
Histological Grade ◽  
System Level ◽  
Clinical Approach ◽  
Cancer Therapies ◽  
Functional Roles ◽  
Network Analyses ◽  
Molecular Events ◽  
Anti Cancer ◽  
Tumor Growth And Metastasis ◽  
Chemotherapy Agents

Background:Chondrosarcomas are cartilaginous tumors that constitute one-third of skeletal system cancers. Chondrosarcomas are capable of transitioning to highly metastatic and treatment-refractory states, resulting in significant patient mortality. However, the molecular events accompanying this behavior remain unknown.Objectives:We aimed to uncover the molecular pathway underlying such tumor progression that confers a higher malignancy to chondrosarcoma.Methods:We conducted unsupervised gene co-expression network analyses using transcriptomes of patients with chondrosarcoma and extracted a characteristic transcription network underlying chondrosarcoma malignancy. By implementing a system-level upstream analysis of this gene network, we identified the transcriptional factor as a key regulator governing chondrosarcoma progression. We unraveled the functional roles of the identified factor in promoting tumor growth and metastasis of chondrosarcomas in the context of their unique microenvironments.Results:By conducting system-level upstream analysis, we identified a factor as a transcriptional regulator that governs the malignancy gene module. The identified factor was upregulated in chondrosarcoma biopsies associated with a high histological grade and conferred chondrosarcoma cells invasiveness and tumor-initiating capacity. In an orthotopic xenograft mouse model, the identified factor modulated local outgrowth and pulmonary metastasis of chondrosarcoma. Pharmacological inhibition of the identified factor in conjunction with the chemotherapy agents such as cisplatin or doxorubicin synergistically enhanced chondrosarcoma cell apoptosis and abolished malignant phenotypes of chondrosarcoma in mice.Conclusion:Our study provides a proof of concept evidence that inhibiting the identified factor suppresses progression of chondrosarcoma and improves the efficacy of chemotherapy in cellular and pre-clinical levels. Taken together, we believe that our findings provide novel molecular insights for the development of new anti-cancer therapies to target chondrosarcomas.References:[1]Gelderblom H, et al. The clinical approach towards chondrosarcoma. Oncologist 13, 320-329 (2008)Disclosure of Interests:None declared

Fault Diagnosis of New Certain Mine Sweeping Plough’s Electrical Control System Based on Data Fusion

2015 ◽  
Vol 713-715 ◽  
pp. 539-543
Author(s):  
Yong Zhao ◽  
Xiao Qiang Yang ◽  
Yin Hua Xu ◽  
Jian Bin Li
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fault Diagnosis ◽  
Data Fusion ◽  
Complex Structure ◽  
Evidence Theory ◽  
System Level ◽  
Sensor Failure ◽  
Advanced Technique ◽  
Electrical Control

The fault diagnosis of electrical control system of certain type mine sweeping vehicle is difficult due to its complex structure and advanced technique. So in the multi-sensor failure diagnosis process, as a result of various reasons, such as the existence of measurement noise, diagnosis knowledge incomplete and so on, it makes the fault diagnosis uncertainty and affects the reliability and the accuracy of the diagnosis result. This article according to the analysis of electrical control system's fault characteristic of the mine sweeping plough’s, proposes a technique based on data fusion fault diagnosis method. The diagnosis process is divided into the sub system and the system-level, the subsystem uses the BP neural network to classify the fault mode, the system-level uses the D-S evidence theory carries on the comprehensive decision judgment for the whole system's fault. Application shows if some sub-neural network diagnosis has error, using D-S evidence theory fusion can effectively improve the accuracy of diagnosis.

scholarly journals Diversity Indices of Plant Communities and Their Rhizosphere Microbiomes: An Attempt to Find the Connection

2021 ◽  
Vol 9 (11) ◽  
pp. 2339
Author(s):  
Aleksei O. Zverev ◽  
Arina A. Kichko ◽  
Aleksandr G. Pinaev ◽  
Nikolay A. Provorov ◽  
Evgeny E. Andronov
Keyword(s):  
Microbial Communities ◽  
Plant Communities ◽  
Plant Diversity ◽  
Beta Diversity ◽  
Mutual Influence ◽  
Plant Root ◽  
Alpha Diversity ◽  
Diversity Indices ◽  
Alpha And Beta Diversity ◽  
Highly Correlated

The rhizosphere community represents an “ecological interface” between plant and soil, providing the plant with a number of advantages. Despite close connection and mutual influence in this system, the knowledge about the connection of plant and rhizosphere diversity is still controversial. One of the most valuable factors of this uncertainty is a rough estimation of plant diversity. NGS sequencing can make the estimations of the plant community more precise than classical geobotanical methods. We investigate fallow and crop sites, which are similar in terms of environmental conditions and soil legacy, yet at the same time are significantly different in terms of plant diversity. We explored amplicons of both the plant root mass (ITS1 DNA) and the microbial communities (16S rDNA); determined alpha- and beta-diversity indices and their correlation, and performed differential abundance analysis. In the analysis, there is no correlation between the alpha-diversity indices of plants and the rhizosphere microbial communities. The beta-diversity between rhizosphere microbial communities and plant communities is highly correlated (R = 0.866, p = 0.01). ITS1 sequencing is effective for the description of plant root communities. There is a connection between rhizosphere communities and the composition of plants, but on the alpha-diversity level we found no correlation. In the future, the connection of alpha-diversities should be explored using ITS1 sequencing, even in more similar plant communities—for example, in different synusia.

scholarly journals Rewetting of Three Drained Peatlands Drives Congruent Compositional Changes in Pro- and Eukaryotic Soil Microbiomes Through Environmental Filtering

2019 ◽  
Author(s):  
Micha Weil ◽  
Haitao Wang ◽  
Mia Bengtsson ◽  
Daniel Köhn ◽  
Anke Günther ◽  
...  
Keyword(s):  
Community Composition ◽  
Ecosystem Respiration ◽  
Abiotic Factors ◽  
Environmental Filtering ◽  
Network Analyses ◽  
Respiration Rates ◽  
Control Community ◽  
Methane Fluxes ◽  
Compositional Changes ◽  
Shed Light

AbstractDrained peatlands are significant sources of the greenhouse gas (GHG) carbon dioxide. Rewetting is a proven strategy to protect carbon stocks; however, it can lead to increased emissions of the potent GHG methane. The response to rewetting of soil microbiomes as drivers of these processes is poorly understood, as are biotic and abiotic factors that control community composition.We analyzed the pro- and eukaryotic microbiomes of three contrasting pairs of minerotrophic fens subject to decade-long drainage and subsequent rewetting. Also, abiotic soil properties including moisture, dissolved organic matter, methane fluxes and ecosystem respiration rates.The composition of the microbiomes was fen-type-specific, but all rewetted sites showed higher abundance of anaerobic taxa compared to drained sites. Based on multi-variate statistics and network analyses we identified soil moisture as major driver of community composition. Furthermore, salinity drove the separation between coastal and freshwater fen communities. Methanogens were more than tenfold more abundant in rewetted than in drained sites, while their abundance was lowest in the coastal fen, likely due to competition with sulfate reducers. The microbiome compositions were reflected in methane fluxes from the sites. Our results shed light on the factors that structure fen microbiomes via environmental filtering.

scholarly journals Vegetation dynamics under non-strong agricultural impact (by the example of Oktyabrsk village environs in the Uchalinskiy District of the Republic of Bashkortostan)

2021 ◽  
Vol 10 (1) ◽  
pp. 121-127
Author(s):  
Nazar Nikolayevich Nazarenko ◽  
Svetlana Yuryevna Batyusheva
Keyword(s):  
Plant Communities ◽  
Vegetation Dynamics ◽  
Vascular Plants ◽  
Abiotic Factors ◽  
Pasture Digression ◽  
Plant Associations ◽  
Republic Of Bashkortostan ◽  
Principal Factors ◽  
The Republic ◽  
Agricultural Impact

Vegetation and its biotopes that are transitional between ruderal and natural ones have been researched in Oktyabrsk village environs (Uchalinskiy District of the Republic of Bashkortostan). The studied vegetation is characterized by rather low biodiversity values and high values of dominance 56 species of vascular plants are identified, 10-species plant communities with 23 clear identified dominant and co-dominant species prevail. Ruderal species are dominant and co-dominant for the majority of plant communities. Fifteen plant associations and specific biotopes have been defined by multivariate statistics methods. The identified associations are phytometers for detected principal abiotic factors. The detected associations form ordination series the authors have identified three biotopical centers (ruderal, birch forest and steppe), three biotopical series and three coenotic series, which are associated with high and temperate pasture loading levels and pasture digression series, forming an integrated succession system of the studied territory. It has been established that principal factors of associations forming is pasture loading level and the principal factors of biotopes forming are soil moistening and its variability, ombroregime (humidification level), termoregime and regime of continentality (temperature-varying amplitude).

scholarly journals Plant and insect herbivore community variation across the Paleocene–Eocene boundary in the Hanna Basin, southeastern Wyoming

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7798
Author(s):  
Lauren E. Azevedo Schmidt ◽  
Regan E. Dunn ◽  
Jason Mercer ◽  
Marieke Dechesne ◽  
Ellen D. Currano
Keyword(s):  
Community Composition ◽  
Plant Communities ◽  
Plant Diversity ◽  
High Water ◽  
Insect Herbivore ◽  
Herbivore Damage ◽  
Late Paleocene ◽  
Hanna Basin ◽  
Laramide Basins ◽  
Herbivore Communities

Ecosystem function and stability are highly affected by internal and external stressors. Utilizing paleobotanical data gives insight into the evolutionary processes an ecosystem undergoes across long periods of time, allowing for a more complete understanding of how plant and insect herbivore communities are affected by ecosystem imbalance. To study how plant and insect herbivore communities change during times of disturbance, we quantified community turnover across the Paleocene­–Eocene boundary in the Hanna Basin, southeastern Wyoming. This particular location is unlike other nearby Laramide basins because it has an abundance of late Paleocene and Eocene coal and carbonaceous shales and paucity of well-developed paleosols, suggesting perpetually high water availability. We sampled approximately 800 semi-intact dicot leaves from five stratigraphic levels, one of which occurs late in the Paleocene–Eocene thermal maximum (PETM). Field collections were supplemented with specimens at the Denver Museum of Nature & Science. Fossil leaves were classified into morphospecies and herbivore damage was documented for each leaf. We tested for changes in plant and insect herbivore damage diversity using rarefaction and community composition using non-metric multidimensional scaling ordinations. We also documented changes in depositional environment at each stratigraphic level to better contextualize the environment of the basin. Plant diversity was highest during the mid-late Paleocene and decreased into the Eocene, whereas damage diversity was highest at the sites with low plant diversity. Plant communities significantly changed during the late PETM and do not return to pre-PETM composition. Insect herbivore communities also changed during the PETM, but, unlike plant communities, rebound to their pre-PETM structure. These results suggest that insect herbivore communities responded more strongly to plant community composition than to the diversity of species present.

Machine learning-assisted imaging analysis of a human epiblast model

2021 ◽  
Author(s):  
Agnes M Resto Irizarry ◽  
Sajedeh Nasr Esfahani ◽  
Yi Zheng ◽  
Robin Zhexuan Yan ◽  
Patrick Kinnunen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Stem Cells ◽  
Cell Tracking ◽  
Complex Structure ◽  
Cyst Formation ◽  
System Level ◽  
Imaging Data ◽  
Cell Level ◽  
Human Blastocyst ◽  
Cell Cell

Abstract The human embryo is a complex structure that emerges and develops as a result of cell-level decisions guided by both intrinsic genetic programs and cell–cell interactions. Given limited accessibility and associated ethical constraints of human embryonic tissue samples, researchers have turned to the use of human stem cells to generate embryo models to study specific embryogenic developmental steps. However, to study complex self-organizing developmental events using embryo models, there is a need for computational and imaging tools for detailed characterization of cell-level dynamics at the single cell level. In this work, we obtained live cell imaging data from a human pluripotent stem cell (hPSC)-based epiblast model that can recapitulate the lumenal epiblast cyst formation soon after implantation of the human blastocyst. By processing imaging data with a Python pipeline that incorporates both cell tracking and event recognition with the use of a CNN-LSTM machine learning model, we obtained detailed temporal information of changes in cell state and neighborhood during the dynamic growth and morphogenesis of lumenal hPSC cysts. The use of this tool combined with reporter lines for cell types of interest will drive future mechanistic studies of hPSC fate specification in embryo models and will advance our understanding of how cell-level decisions lead to global organization and emergent phenomena. Insight, innovation, integration: Human pluripotent stem cells (hPSCs) have been successfully used to model and understand cellular events that take place during human embryogenesis. Understanding how cell–cell and cell–environment interactions guide cell actions within a hPSC-based embryo model is a key step in elucidating the mechanisms driving system-level embryonic patterning and growth. In this work, we present a robust video analysis pipeline that incorporates the use of machine learning methods to fully characterize the process of hPSC self-organization into lumenal cysts to mimic the lumenal epiblast cyst formation soon after implantation of the human blastocyst. This pipeline will be a useful tool for understanding cellular mechanisms underlying key embryogenic events in embryo models.

Competition between native and non-native plants.

2020 ◽  
pp. 291-307
Author(s):  
Elizabeth M. Wandrag ◽  
◽  
Jane A. Catford ◽  
◽  
◽  
...  
Keyword(s):  
Plant Species ◽  
Plant Communities ◽  
Native Species ◽  
Abiotic Factors ◽  
Invasion Biology ◽  
Competitive Interactions ◽  
Native Plant ◽  
Native Plant Species ◽  
New Locations ◽  
Strength Of Competition

The introduction of species to new locations leads to novel competitive interactions between resident native and newly-arriving non-native species. The nature of these competitive interactions can influence the suitability of the environment for the survival, reproduction and spread of non-native plant species, and the impact those species have on native plant communities. Indeed, the large literature on competition among plants reflects its importance in shaping the composition of plant communities, including the invasion success of non-native species. While competition and invasion theory have historically developed in parallel, the increasing recognition of the synergism between the two themes has led to new insights into how non-native plant species invade native plant communities, and the impacts they have on those plant communities. This chapter provides an entry point into the aspects of competition theory that can help explain the success, dominance and impacts of invasive species. It focuses on resource competition, which arises wherever the resources necessary for establishment, survival, reproduction and spread are in limited supply. It highlights key hypotheses developed in invasion biology that relate to ideas of competition, outlines biotic and abiotic factors that influence the strength of competition and species' relative competitive abilities, and describes when and how competition between non-native and native plant species can influence invasion outcomes. Understanding the processes that influence the strength of competition between non-native and native plant species is a necessary step towards understanding the causes and consequences of biological invasions.

scholarly journals Soil Microbial Biomass and Community Composition Relates to Poplar Genotypes and Environmental Conditions

Forests ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 262 ◽  
Author(s):  
Leszek Karliński ◽  
Sabine Ravnskov ◽  
Maria Rudawska
Keyword(s):  
Microbial Biomass ◽  
Microbial Communities ◽  
Community Composition ◽  
Soil Depth ◽  
Abiotic Factors ◽  
Soil Conditions ◽  
Main Role ◽  
Site Factors ◽  
Host Genotype ◽  
The Impact

Poplars, known for their diversity, are trees that can develop symbiotic relationships with several groups of microorganisms. The genetic diversity of poplars and different abiotic factors influence the properties of the soil and may shape microbial communities. Our study aimed to analyse the impact of poplar genotype on the biomass and community composition of the microbiome of four poplar genotypes grown under different soil conditions and soil depths. Of the three study sites, established in the mid-1990s, one was near a copper smelter, whereas the two others were situated in unpolluted regions, but were differentiated according to the physicochemical traits of the soil. The whole-cell fatty acid analysis was used to determine the biomass and proportions of gram-positive, gram-negative and actinobacteria, arbuscular fungi (AMF), other soil fungi, and protozoa in the whole microbial community in the soil. The results showed that the biomass of microorganisms and their contributions to the community of organisms in the soil close to poplar roots were determined by both factors: the tree-host genotype and the soil environment. However, each group of microorganisms was influenced by these factors to a different degree. In general, the site effect played the main role in shaping the microbial biomass (excluding actinobacteria), whereas tree genotype determined the proportions of the fungal and bacterial groups in the microbial communities and the proportion of AMF in the fungal community. Bacterial biomass was influenced more by site factors, whereas fungal biomass more by tree genotype. With increasing soil depth, a decrease in the biomass of all microorganisms was observed; however, the proportions of the different microorganisms within the soil profile were the result of interactions between the host genotype and soil conditions. Despite the predominant impact of soil conditions, our results showed the important role of poplar genotype in shaping microorganism communities in the soil.

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