An Incremental Model Projection Applied to Streamline Software Architecture Assessment and Monitoring

Managing software architecture represents a big challenge throughout the development lifecycle. The complexity of the involved structural elements and the relations among them make the specified models look oversized and fuzzy, which makes the architecture incomprehensible, hard to maintain, and difficult to assess its quality. This paper's goal is to propose a powerful methodology for simplifying and reducing models' complexity to increase understandability, smoothing maintenance, and facilitating architecture monitoring and assessment. For this purpose, the authors rely heavily on two major concepts, multi-view modeling, and incremental model projection. The multi-viewing requires that all models must have two main views to describe the architecture and the mapping to its relevant quality attributes. The incremental projection is a methodology used to specialize and minimize models progressively to make them simpler and clearer. The results show that projecting models incrementally can reduce and narrow them significantly.

A novel method for assessing climate change impacts in ecotron experiments

Ecotron facilities allow accurate control of many environmental variables coupled with extensive monitoring of ecosystem processes. They therefore require multivariate perturbation of climate variables, close to what is observed in the field and projections for the future. Here, we present a new method for creating realistic climate forcing for manipulation experiments and apply it to the UHasselt Ecotron experiment. The new methodology uses data derived from the best available regional climate model projection and consists of generating climate forcing along a gradient representative of increasingly high global mean air temperature anomalies. We first identified the best-performing regional climate model simulation for the ecotron site from the Coordinated Regional Downscaling Experiment in the European domain (EURO-CORDEX) ensemble based on two criteria: (i) highest skill compared to observations from a nearby weather station and (ii) representativeness of the multi-model mean in future projections. The time window is subsequently selected from the model projection for each ecotron unit based on the global mean air temperature of the driving global climate model. The ecotron units are forced with 3-hourly output from the projections of the 5-year period in which the global mean air temperature crosses the predefined values. With the new approach, Ecotron facilities become able to assess ecosystem responses on changing climatic conditions, while accounting for the co-variation between climatic variables and their projection in variability, well representing possible compound events. The presented methodology can also be applied to other manipulation experiments, aiming at investigating ecosystem responses to realistic future climate change.

Carbon Balance of Grasslands on the Qinghai-Tibet Plateau under Future Climate Change: A Review

Climate change has brought significant impacts upon the natural ecological environment and human social development. The future carbon balance study has become an important part of research on the impacts of climate change. The Qinghai-Tibet Plateau (QTP) is a key area for studying climate change. Grassland, as a typical ecosystem of the QTP, embodies the sensitivity of the plateau to the climatic environment, so the carbon balance of grassland under future climate change conditions is important for studying global change. This paper reviewed the literature on carbon balance projection of grassland on the QTP under climate change. Two types of research methods were used to analyze and discuss the studies’ results, including experimental scenario projection and model projection. The experiment projected that appropriate temperature and moisture could enhance the carbon sink capacity of a grassland ecosystem, where moisture played a leading role. The model projection results showed that the carbon balance under different spatial and temporal scales were different. Although both can project the carbon balance of the study area, there are still some uncertainties. In addition, this research area should also consider the influence of human activity and plateau pikas to more accurately project the future carbon balance.