Analysis of behaviour patterns and thermal responses to a hot–arid climate in rural China

Climate can greatly affect building design, life style and thermal perception for all groups of people; however, this phenomenon has not yet been rigorously evaluated in China's hot–arid climate. The aim of this paper is to present the results of a thermal comfort survey by evaluating the influence of the hot–arid climate upon the behavioural patterns and thermal comfort responses of 160 residents in 65 traditional vernacular houses in Turfan, China, in 2011. In this survey, there were 206 sets of effective data, and the features of the traditional residential buildings and the human behaviour patterns in Turfan were described and analysed. The results showed that the diversified courtyards and shade spaces were the most obvious features of traditional houses in Turfan. People here typically spend most of their time in one of two spaces for eating, resting, and entertaining. It was found that the preferred temperature was 26.5 °C. The preferred air velocity occurred at 0.62 m/s. A suitable air velocity range of 0.15–1.24 m/s was suggested in Turfan. Moreover, the neutral temperature of the local people was 30.1 °C (t_g or t_o). The upper limits of the 80% acceptable zone by using the direct and indirect acceptability method were 32.7 and 33.8 °C, respectively. The neutral temperature and upper limit of the acceptable zone in Turfan were higher than those of the adaptive standards. Attention should be paid to the role of thermal comfort in influencing building design by using simple passive cooling strategies. The above results are believed to be potentially valuable for the design and evaluation of residential buildings located in hot–arid climate.     

Invasion of woody species into temperate grasslands: Relationship with abiotic and biotic soil resource heterogeneity

Question: Invasion of woody species into grasslands is a global phenomenon. This is also topical in semi‐natural temperate grasslands that are no longer profitable for agricultural management. Trees and grasses interact through harsh root competition, but below‐ground processes have been neglected in the dynamics of semi‐natural grasslands. Trees are thought to have a competitive advantage in resource‐rich and heterogeneous soils. We tested whether soil resource quantity and heterogeneity differ between paired temperate semi‐natural grasslands and forests (former grasslands), and whether this was caused abiotically by varying soil depth or biotically by fine roots. Location: Thin‐soil calcareous alvar grasslands with overgrown parts (young Pinus sylvestris forests) in W. Estonia. Methods: The quantity and spatial heterogeneity of soil resources (moisture and nutrients), soil depth, and root parameters (mass, length and specific length) were measured in 1‐m transects of 11 samples in 26 paired grasslands and forests. The quantity and heterogeneity of soil resources were compared between vegetation types and related to soil depth and root parameters. Results: Soil resources were lower and more heterogeneous in forests than in grasslands. The invasion of woody species was enhanced abiotically by deeper soil. Root mass was larger in the forests, but root length was longer in the grasslands. Both root mass and specific root length were more heterogeneous in the forests. Forest root length was negatively correlated with transient soil moisture patches and positively correlated with more persistent nutrient‐rich patches. No such relationship was found in grasslands. Conclusions: Abiotic soil heterogeneity (local deep‐soil patches) supports woody species invasion, but the trees themselves also biotically make soils more heterogeneous, which further enhances woody species invasion. Large trees use soil resources patchily, making soils biotically poorer and more heterogeneous in resources. The dynamics of temperate semi‐natural grasslands are strongly linked to below‐ground ecological processes, and high soil heterogeneity can be both the cause and the outcome of woody species invasion.     

Markov and Semi‐Markov Switching Linear Mixed Models Used to Identify Forest Tree Growth Components

Summary Tree growth is assumed to be mainly the result of three components: (i) an endogenous component assumed to be structured as a succession of roughly stationary phases separated by marked change points that are asynchronous among individuals, (ii) a time‐varying environmental component assumed to take the form of synchronous fluctuations among individuals, and (iii) an individual component corresponding mainly to the local environment of each tree. To identify and characterize these three components, we propose to use semi‐Markov switching linear mixed models, i.e., models that combine linear mixed models in a semi‐Markovian manner. The underlying semi‐Markov chain represents the succession of growth phases and their lengths (endogenous component) whereas the linear mixed models attached to each state of the underlying semi‐Markov chain represent—in the corresponding growth phase—both the influence of time‐varying climatic covariates (environmental component) as fixed effects, and interindividual heterogeneity (individual component) as random effects. In this article, we address the estimation of Markov and semi‐Markov switching linear mixed models in a general framework. We propose a Monte Carlo expectation–maximization like algorithm whose iterations decompose into three steps: (i) sampling of state sequences given random effects, (ii) prediction of random effects given state sequences, and (iii) maximization. The proposed statistical modeling approach is illustrated by the analysis of successive annual shoots along Corsican pine trunks influenced by climatic covariates.