Modeling of an Integrated Renewable-Energy-Based System for Heating, Cooling, and Electricity for Buildings

An integrated numerical model that describes the operation of a renewable-energy-based system for a building’s heating, cooling, and domestic hot water needs is described in this study. The examined energy system includes a vapor compression multi-source heat pump, PVT collectors, borehole thermal energy storage, and water tanks. Energy balance equations for the collectors and the tanks are coupled with correlations for the heat pump and the piping losses within a thermal network approach. The non-linear system of equations that arises is solved by employing in-house software developed in Python v. 3.7.3. The performance of the numerical tool is validated against measurements collected during the pilot operation of such a system installed in Athens (Greece) for two 5-day periods (summer and winter). It is shown that the proposed model can predict, both qualitatively and quantitatively, the building’s energy system performance, whereas limited deviations from the experimental findings are mostly observed when highly transient phenomena occur. The numerical tool is designed with flexibility in mind and can be easily adapted to accommodate additional energy-system configurations and operational modes. Thus, it can be utilized as a supporting decision tool for new energy systems’ designs and the optimization of existing ones

Collective and harmonised high throughput barcoding of insular arthropod biodiversity: toward a Genomic Observatories Network for islands

Current understanding of ecological and evolutionary processes underlying island biodiversity is heavily shaped by empirical data from plants and birds, although arthropods comprise the overwhelming majority of known animal species, and as such can provide key insights into processes governing biodiversity. Novel high throughput sequencing (HTS) approaches are now emerging as powerful tools to overcome limitations in the availability of arthropod biodiversity data, and hence provide insights into these processes. Here we explore how these tools might be most effectively exploited for comprehensive and comparable inventory and monitoring of insular arthropod biodiversity. We first review the strengths, limitations and potential synergies among existing approaches of high throughput barcode sequencing. We consider how this can be complemented with deep learning approaches applied to image analysis to study arthropod biodiversity. We then explore how these approaches can be implemented within the framework of an island Genomic Observatories Network (iGON) for the advancement of fundamental and applied understanding of island biodiversity. To this end, we identify seven island biology themes at the interface of ecology, evolution and conservation biology, within which collective and harmonised efforts in HTS arthropod inventory could yield significant advances in island biodiversity research

Towards a genetic theory of island biogeography: Inferring processes from multidimensional community-scale data

Background: MacArthur and Wilson's theory of island biogeography has been a foundation for obtaining testable predictions from models of community assembly and for developing models that integrate across scales and disciplines. Historically, however, these developments have focused on integration across ecological and macroevolutionary scales and on predicting patterns of species richness, abundance distributions, trait data and/or phylogenies. The distribution of genetic variation across species within a community is an emerging pattern that contains signatures of past population histories, which might provide an historical lens for the study of contemporary communities. As intraspecific genetic diversity data become increasingly available at the scale of entire communities, there is an opportunity to integrate microevolutionary processes into our models, moving towards development of a genetic theory of island biogeography. Motivation/goal: We aim to promote the development of process-based biodiversity models that predict community genetic diversity patterns together with other community-scale patterns. To this end, we review models of ecological, microevolutionary and macroevolutionary processes that are best suited to the creation of unified models, and the patterns that these predict. We then discuss ongoing and potential future efforts to unify models operating at different organizational levels, with the goal of predicting multidimensional community-scale data including a genetic component. Main conclusions: Our review of the literature shows that despite recent efforts, further methodological developments are needed, not only to incorporate the genetic component into existing island biogeography models, but also to unify processes across scales of biological organization. To catalyse these developments, we outline two potential ways forward, adopting either a top-down or a bottom-up approach. Finally, we highlight key ecological and evolutionary questions that might be addressed by unified models including a genetic component and establish hypotheses about how processes across scales might impact patterns of community genetic diversity