Dataset Information

Spatial-Temporal Changes and Associated Determinants of Global Heating Degree Days.

ABSTRACT: The heating degree days (HDDs) could indicate the climate impact on energy consumption and thermal environment conditions effectively during the winter season. Nevertheless, studies on the spatial-temporal changes in global HDDs and their determinants are scarce. This study used multi-source data and several methods to explore the rules of the spatial distribution of global HDDs and their interannual changes over the past 49 years and some critical determinants. The results show that global HDDs generally became larger in regions with higher latitudes and altitudes. Most global change rates of HDDs were negative (p < 0.10) and decreased to a greater extent in areas with higher latitudes. Most global HDDs showed sustainability trends in the future. Both the HDDs and their change rates were significantly partially correlated with latitude, altitude, mean albedo, and EVI during winter, annual mean PM_2.5 concentration, and nighttime light intensity (p = 0.000). The HDDs and their change rates could be simulated well by the machine learning method. Their RMSEs were 564.08 °C * days and 3.59 °C * days * year^-1, respectively. Our findings could support the scientific response to climate warming, the construction of living environments, sustainable development, etc.

SUBMITTER: Li Y

PROVIDER: S-EPMC8229943 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Publications

Spatial-Temporal Changes and Associated Determinants of Global Heating Degree Days.

Li Yuanzheng Y Li Jinyuan J Xu Ao A Feng Zhizhi Z Hu Chanjuan C Zhao Guosong G

International journal of environmental research and public health 20210608 12

The heating degree days (HDDs) could indicate the climate impact on energy consumption and thermal environment conditions effectively during the winter season. Nevertheless, studies on the spatial-temporal changes in global HDDs and their determinants are scarce. This study used multi-source data and several methods to explore the rules of the spatial distribution of global HDDs and their interannual changes over the past 49 years and some critical determinants. The results show that global HDDs ...[more]

PMID: 34201057

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Project description:The biennial plant Gentianella bohemica is a subendemic of the Bohemian Massif, where it occurs in seminatural grasslands. It has become rare in recent decades as a result of profound changes in land use. Using amplified fragment length polymorphisms (AFLP) fingerprint data, we investigated the genetic structure within and among populations of G. bohemica in Bavaria, the Czech Republic, and the Austrian border region. The aim of our study was (1) to analyze the genetic structure among populations and to discuss these findings in the context of present and historical patterns of connectivity and isolation of populations, (2) to analyze genetic structure among consecutive generations (cohorts of two consecutive years), and (3) to investigate relationships between intrapopulational diversity and effective population size (N(e)) as well as plant traits. (1) The German populations were strongly isolated from each other (pairwise F(ST)= 0.29-0.60) and from all other populations (F(ST)= 0.24-0.49). We found a pattern of near panmixis among the latter (F(ST)= 0.15-0.35) with geographical distance explaining only 8% of the genetic variance. These results were congruent with a principal coordinate analysis (PCoA) and analysis using STRUCTURE to identify genetically coherent groups. These findings are in line with the strong physical barrier and historical constraints, resulting in separation of the German populations from the others. (2) We found pronounced genetic differences between consecutive cohorts of the German populations (pairwise F(ST)= 0.23 and 0.31), which can be explained by local population history (land use, disturbance). (3) Genetic diversity within populations (Shannon index, H(Sh)) was significantly correlated with N(e) (R(S)= 0.733) and reflected a loss of diversity due to several demographic bottlenecks. Overall, we found that the genetic structure in G. bohemica is strongly influenced by historical periods of high connectivity and isolation as well as by marked demographic fluctuations in declining populations.

Dataset Information

Spatial-Temporal Changes and Associated Determinants of Global Heating Degree Days.

Publications

Spatial-Temporal Changes and Associated Determinants of Global Heating Degree Days.

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