Soil Micro-eukaryotic Diversity Patterns Along Elevation Gradient Are Best Estimated by Increasing the Number of Elevation Steps Rather than Within Elevation Band Replication.

The development of high-throughput sequencing (HTS) of environmental DNA (eDNA) has stimulated the study of soil microbial diversity patterns and drivers at all scales. However, given the heterogeneity of soils, a challenge is to define effective and efficient sampling protocols that allow sound comparison with other records, especially vegetation. In studies of elevational diversity pattern, a trade-off is choosing between replication within elevation bands vs. sampling more elevation bands. We addressed this question for soil protists along an elevation gradient on Mt. Asahi, Hokkaido, Japan. We compared two sampling approaches: (1) the replicate strategy (five replicates at six elevational bands, total = 30) and (2) the transect strategy (one sample in each of 16 different elevational bands). Despite a nearly twofold lower sampling effort, the transect strategy yielded congruent results compared to the replicate strategy for the estimation of elevational alpha diversity pattern: the regression coefficients between diversity indices and elevation did not differ between the two options. Furthermore, for a given total number of samples, gamma diversity estimated across the entire transect was higher when sampling more elevational bands as compared to replication from fewer elevational bands. Beta diversity (community composition turnover) was lower within a given elevational band than between adjacent bands and increased with elevation distance. In redundancy analyses, soil organic matter-related variable (the first principal component of soil organic matter, water content, total organic carbon, and nitrogen by whom were highly correlated) and elevation best explained elevational beta diversity pattern for both sampling approaches. Taken together, our results suggest that sampling a single plot per elevation band will be sufficient to obtain a good estimate of soil micro-eukaryotic diversity patterns along elevation gradients. This study demonstrated the effectiveness of the transect strategy in estimating diversity patterns along elevation gradients which is instructive for future environmental or even experimental studies. While not advocating for completely replacing replication-based sampling practices, it is important to note that both replicate and transect strategies have their merits and can be employed based on specific research goals and resource limitations.

Occurrence-based diversity estimation reveals macroecological and conservation knowledge gaps for global woody plants.

Incomplete sampling of species' geographic distributions has challenged biogeographers for many years to precisely quantify global-scale biodiversity patterns. After correcting for the spatial inequality of sample completeness, we generated a global species diversity map for woody angiosperms (82,974 species, 13,959,780 occurrence records). The standardized diversity estimated more pronounced latitudinal and longitudinal diversity gradients than the raw data and improved the spatial prediction of diversity based on environmental factors. We identified areas with potentially high species richness and rarity that are poorly explored, unprotected, and threatened by increasing human pressure: They are distributed mostly at low latitudes across central South America, Central Africa, subtropical China, and Indomalayan islands. These priority areas for botanical exploration can help to efficiently fill spatial knowledge gaps for better describing the status of biodiversity and improve the effectiveness of the protected area network for global woody plant conservation.

Multiple drivers of the COVID-19 spread: The roles of climate, international mobility, and region-specific conditions.

Following its initial appearance in December 2019, coronavirus disease 2019 (COVID-19) quickly spread around the globe. Here, we evaluated the role of climate (temperature and precipitation), region-specific COVID-19 susceptibility (BCG vaccination factors, malaria incidence, and percentage of the population aged over 65 years), and human mobility (relative amounts of international visitors) in shaping the geographical patterns of COVID-19 case numbers across 1,020 countries/regions, and examined the sequential shift that occurred from December 2019 to June 30, 2020 in multiple drivers of the cumulative number of COVID-19 cases. Our regression model adequately explains the cumulative COVID-19 case numbers (per 1 million population). As the COVID-19 spread progressed, the explanatory power (R2) of the model increased, reaching > 70% in April 2020. Climate, host mobility, and host susceptibility to COVID-19 largely explained the variance among COVID-19 case numbers across locations; the relative importance of host mobility and that of host susceptibility to COVID-19 were both greater than that of climate. Notably, the relative importance of these factors changed over time; the number of days from outbreak onset drove COVID-19 spread in the early stage, then human mobility accelerated the pandemic, and lastly climate (temperature) propelled the phase following disease expansion. Our findings demonstrate that the COVID-19 pandemic is deterministically driven by climate suitability, cross-border human mobility, and region-specific COVID-19 susceptibility. The identification of these multiple drivers of the COVID-19 outbreak trajectory, based on mapping the spread of COVID-19, will contribute to a better understanding of the COVID-19 disease transmission risk and inform long-term preventative measures against this disease.

Integrating multiple sources of ecological data to unveil macroscale species abundance.

The pattern of species abundance, represented by the number of individuals per species within an ecological community, is one of the fundamental characteristics of biodiversity. However, despite their obvious significance in ecology and biogeography, there is still no clear understanding of these patterns at large spatial scales. Here, we develop a hierarchical modelling approach to estimate macroscale patterns of species abundance. Using this approach, estimates of absolute abundance of 1248 woody plant species at a 10-km-grid-square resolution over East Asian islands across subtropical to temperate biomes are obtained. We provide two examples of the basic and applied use of the estimated species abundance for (1) inference of macroevolutionary processes underpinning regional biodiversity patterns and (2) quantitative community-wide assessment of a national red list. These results highlight the potential of the elucidation of macroscale species abundance that has thus far been an inaccessible but critical property of biodiversity.