Contrasting the co-variability of daytime cloud and precipitation over tropical land and ocean

Determinants of Genetic Structure in a Highly Heterogeneous Landscape in Southwest China

Intra-specific genetic diversity is a fundamental component of biodiversity, and is key to species adaptation and persistence. However, significant knowledge gaps still exist in our understanding of the patterns of genetic diversity and their key determinants. Most previous investigations mainly utilized single-species and/or a limited number of explanatory variables; so here we mapped the patterns of plastid genetic diversity within 15 plant species, and explored the key determinants shaping these patterns using a wide range of variables. Population-level cpDNA sequence data for 15 plant species from the Longitudinal Range Gorge Region (LRGR), southwest China, were retrieved from literature and used to estimate haplotype diversity (H _D) and population pairwise genetic differentiation (F _ST) indices. Genetic diversity and divergence landscape surfaces were then generated based on the H _D and F _ST, respectively, to clarify the patterns of genetic structure in the region. Subsequently, we analyzed the relationships between plastid genetic diversity and 16 explanatory variables (classified as anthropogenic, climatic, and topographic). We found that the highest genetic diversity occurred in the Yulong Mountain region, with a significant proportion (~74.81%) of the high diversity land area being located outside of protected areas. The highest genetic divergence was observed approximately along the 25°N latitudinal line, with notable peaks in the western and eastern edges of the LRGR. Genetic diversity (H _D) was weakly but significantly positively correlated with both Latitude (lat) and Annual Mean Wet Day Frequency (wet), yet significantly negatively correlated with all of Longitude (long), Annual Mean Cloud Cover Percent (cld), Annual Mean Anthropogenic Flux (ahf), and Human Footprint Index (hfp). A combination of climatic, topographic, and anthropogenic factors explained a significant proportion (78%) of genetic variation, with topographic factors (lat and long) being the best predictors. Our analysis identified areas of high genetic diversity (genetic diversity "hotspots") and divergence in the region, and these should be prioritized for conservation. This study contributes to a better understanding of the features that shape the distribution of plastid genetic diversity in the LRGR and thus would inform conservation management efforts in this species-rich, but vulnerable region.

Large-scale Characteristics of Tropical Convective Systems through the Prism of Cloud Regime

We employ the Cloud Regime (CR) concept to identify large-scale tropical convective systems and investigate their characteristics in terms of organization and precipitation. The tropical CRs (TCRs) are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Cloud Optical Thickness (COT) and Cloud Top Pressure (CTP) two-dimensional joint histograms. We focus on the TCRs that have relatively low CTPs and high COTs, as well as heavy precipitation, namely TCR1 (convective core-dominant), TCR2 (various high clouds), and TCR3 (anvils). The horizontal size of aggregates of TCR1, 2, or 3 occurrences (TCR123) is identified as the number of contiguous 1°×1° grid cells occupied by either of these three TCRs. For the small to intermediate size aggregates (TCR123 size 20 to 160 one-degree grid cells), there is large variability in the fraction of the aggregate each TCR occupies, but generally TCR2 exhibits the highest fraction. As the total system size grows, the variability shrinks and for the largest systems ratios eventually converge to 0.3, 0.2, and 0.5 for TCR1, 2, and 3, respectively. The mean precipitation of convective core-rich TCR1 is generally high for the systems of intermediate size (80-160 one-degree grid cells), but with the highest mean coming from smaller systems of 20-40 grid cells. For the largest systems, their mean precipitation in areas containing cores (TCR1) are relatively low with suppressed variation. The mean precipitation rates of TCR2 and TCR3 in a TCR123 aggregate tend to be stronger when accompanying TCR1 mean precipitation rate is also high.