The current state of the use of large wood in river restoration and management

Trees fall naturally into rivers generating flow heterogeneity, inducing geomorphological features, and creating habitats for biota. Wood is increasingly used in restoration projects and the potential of wood acting as leaky barriers to deliver natural flood management by “slowing the flow” is recognised. However, wood in rivers can pose a risk to infrastructure and locally increase flood hazards. The aim of this paper is to provide an up-to-date summary of the benefits and risks associated with using wood to promote geomorphological processes to restore and manage rivers. This summary was developed through a workshop that brought together academics, river managers, restoration practitioners and consultants in the UK to share science and best-practice on wood in rivers. A consensus was developed on four key issues: (i) hydro-geomorphological effects, (ii) current use in restoration and management, (iii) uncertainties and risks, and (iv) tools and guidance required to inform process-based restoration and management

Stochastic flowering phenology in Dactylis Glomerata populations described by Markov chain modelling

Understanding the relationship between flowering patterns and pollen dispersal is important in climate change modelling, pollen forecasting, forestry and agriculture. Enhanced understanding of this connection can be gained through detailed spatial and temporal flowering observations on a population level, combined with modelling simulating the dynamics. Species with large distribution ranges, long flowering seasons, high pollen production and naturally large populations can be used to illustrate these dynamics. Revealing and simulating species-specific demographic and stochastic elements in the flowering process will likely be important in determining when pollen release is likely to happen in flowering plants. Spatial and temporal dynamics of eight populations of Dactylis glomerata were collected over the course of two years to determine high-resolution demographic elements. Stochastic elements were accounted for using Markov Chain approaches in order to evaluate tiller-specific contribution to overall population dynamics. Tiller-specific developmental dynamics were evaluated using three different RV matrix correlation coefficients. We found that the demographic patterns in population development were the same for all populations with key phenological events differing only by a few days over the course of the seasons. Many tillers transitioned very quickly from non-flowering to full flowering, a process that can be replicated with Markov Chain modelling. Our novel approach demonstrates the identification and quantification of stochastic elements in the flowering process of D. glomerata, an element likely to be found in many flowering plants. The stochastic modelling approach can be used to develop detailed pollen release models for Dactylis, other grass species and probably other flowering plants