Determining the role of environmental factors and disturbance in the distribution of reed canary grass within wetlands

Reed canary grass (Phalaris arundinacea L.) is an invasive species originally from Europe that has now expanded to a large range within the United States. Reed canary grass possesses a number of traits that allow it to thrive in a wide range of environmental factors, including high rates of sedimentation, bouts of flooding, and high levels of nutrient inputs. Therefore, the goals of our study were to determine if 1) certain types of wetland were more susceptible to Reed canary grass invasion, and 2) disturbances facilitated Reed canary grass invasion. This study was conducted within the Keweenaw Bay Indian Community reservation in the Upper Peninsula of Michigan, in Baraga County. We selected 28 wetlands for analysis. At each wetland, we identified and sampled distinct vegetative communities and their corresponding environmental attributes, which included water table depth, pH, conductivity, calcium and magnesium concentrations, and percent organic matter. Disturbances at each site were catalogued and their severity estimated with the aid of aerial photos. A GIS dataset containing information about the location of Reed canary grass within the study wetlands, the surrounding roads and the level of roadside Reed canary grass invasion was also developed. In all, 287 plant species were identified and classified into 16 communities, which were then further grouped into three broad groupings of wetlands: nonforested graminoid, Sphagnum peatlands, and forested wetlands. The two most common disturbances identified were roads and off-road recreation trails, both occurring at 23 of the 28 sites. Logging activity surrounding the wetlands was the next most common disturbance and was found at 18 of the sites. Occurrence of Reed canary grass was most common in the non-forested graminoid communities. Reed canary grass was very infrequent in forested wetlands, and almost never occurred in the Sphagnum peatlands. Disturbance intensity was the most significant environmental factor in explaining Reed canary grass occurrence within wetlands. Statistically significant relationships were identified at distances of 1000 m, 500 m, and 250 m from studied wetlands, between the level of road development and the severity of Reed canary grass invasion along roadsides. Further analysis revealed a significant relationship between roadside Reed canary grass populations and the level of road development (e.g. paved, graded, and ungraded).

DISSECTION OF STRESS RESPONSE NETWORKS REGULATING MULTIPLE STRESSES IN RICE

Important food crops like rice are constantly exposed to various stresses that can have devastating effect on their survival and productivity. Being sessile, these highly evolved organisms have developed elaborate molecular machineries to sense a mixture of stress signals and elicit a precise response to minimize the damage. However, recent discoveries revealed that the interplay of these stress regulatory and signaling molecules is highly complex and remains largely unknown. In this work, we conducted large scale analysis of differential gene expression using advanced computational methods to dissect regulation of stress response which is at the heart of all molecular changes leading to the observed phenotypic susceptibility. One of the most important stress conditions in terms of loss of productivity is drought. We performed genomic and proteomic analysis of epigenetic and miRNA mechanisms in regulation of drought responsive genes in rice and found subsets of genes with striking properties. Overexpressed genesets included higher number of epigenetic marks, miRNA targets and transcription factors which regulate drought tolerance. On the other hand, underexpressed genesets were poor in above features but were rich in number of metabolic genes with multiple co-expression partners contributing majorly towards drought resistance. Identification and characterization of the patterns exhibited by differentially expressed genes hold key to uncover the synergistic and antagonistic components of the cross talk between stress response mechanisms. We performed meta-analysis on drought and bacterial stresses in rice and Arabidopsis, and identified hundreds of shared genes. We found high level of conservation of gene expression between these stresses. Weighted co-expression network analysis detected two tight clusters of genes made up of master transcription factors and signaling genes showing strikingly opposite expression status. To comprehensively identify the shared stress responsive genes between multiple abiotic and biotic stresses in rice, we performed meta-analyses of microarray studies from seven different abiotic and six biotic stresses separately and found more than thirteen hundred shared stress responsive genes. Various machine learning techniques utilizing these genes classified the stresses into two major classes' namely abiotic and biotic stresses and multiple classes of individual stresses with high accuracy and identified the top genes showing distinct patterns of expression. Functional enrichment and co-expression network analysis revealed the different roles of plant hormones, transcription factors in conserved and non-conserved genesets in regulation of stress response.