New evidence of the reproductive organs of Glossopteris based on permineralized fossils from Queensland, Australia. II: pollen-bearing organ Ediea gen. nov

Ediea homevalensis H. Nishida, Kudo, Pigg & Rigby gen. et sp. nov. is proposed for permineralized pollen-bearing structures from the Late Permian Homevale Station locality of the Bowen Basin, Queensland, Australia. The taxon represents unisexual fertile shoots bearing helically arranged leaves on a central axis. The more apical leaves are fertile microsporophylls bearing a pair of multi-branched stalks on their adaxial surfaces that each supports a cluster of terminally borne pollen sacs. Proximal to the fertile leaves there are several rows of sterile scale-like leaves. The pollen sacs (microsporangia) have thickened and dark, striate walls that are typical of the Arberiella type found in most pollen organs presumed to be of glossopterid affinity. An examination of pollen organs at several developmental stages, including those containing in situ pollen of the Protohaploxypinus type, provides the basis for a detailed analysis of these types of structures, which bear similarities to both compression/impression Eretmonia-type glossopterid microsporangiate organs and permineralized Eretmonia macloughlinii from Antarctica. These fossils demonstrate that at least some Late Permian pollen organs were simple microsporophyll-bearing shoot systems and not borne directly on Glossopteris leaves.

Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

Proteomic identification of putative microRNA394 target genes in Arabidopsis thaliana identifies MLP family members critical for normal development

Expression of the F-Box protein Leaf Curling Responsiveness (LCR) is regulated by microRNA, miR394, and alterations to this interplay in Arabidopsis thaliana produce defects in leaf polarity and shoot apical meristem (SAM) organisation. Although the miR394-LCR node has been documented in Arabidopsis, the identification of proteins targeted by LCR F-box itself has proven problematic. Here, a proteomic analysis of shoot apices from plants with altered LCR levels identified a member of the Major Latex Protein (MLP) family gene as a potential LCR F-box target. Bioinformatic and molecular analyses also suggested that other MLP family members are likely to be targets for this post-translational regulation. Direct interaction between LCR F-Box and MLP423 was validated. Additional MLP members had reduction in protein accumulation, in varying degrees, mediated by LCR F-Box. Transgenic Arabidopsis lines, in which MLP28 expression was reduced through an artificial miRNA technology, displayed severe developmental defects, including changes in leaf patterning and morphology, shoot apex defects, and eventual premature death. These phenotypic characteristics resemble those of Arabidopsis plants modified to over-express LCR. Taken together, the results demonstrate that MLPs are driven to degradation by LCR, and indicate that MLP gene family is target of miR394-LCR regulatory node, representing potential targets for directly post-translational regulation mediated by LCR F-Box. In addition, MLP28 family member is associated with the LCR regulation that is critical for normal Arabidopsis development.