ABSTRACT
Big-sized trees, species diversity, and stand density affect aboveground biomass in natural tropical and temperate forests. However, these relationships are unclear in arid natural forests and plantations. Here, we hypothesized that large plants (a latent variable of tall-stature and big-crown, which indicated the effect of big-sized trees on ecosystem function and structure) enhance aboveground biomass in both arid natural forests and plantations along the gradients of climate water availability and soil fertility. To prove it, we used structural equation modeling (SEM) to test the influences of large plants located in 20% of the sequence formed by individual size (a synthetical value calculated from tree height and crown) on aboveground biomass in natural forests and plantations while considering the direct and indirect influences of species diversity as well as climatic and soil conditions, using data from 73 natural forest and 30 plantation plots in the northwest arid region of China. The results showed that large plants, species diversity, and stand density all increased aboveground biomass. Soil fertility declined aboveground biomass in natural forest, whereas it increased biomass in plantation. Although climatic water availability had no direct impact on aboveground biomass in both forests, it indirectly controlled the change of aboveground biomass via species diversity, stand density, and large plants. Stand density negatively affects large plants in both natural forests and plantations. Species diversity positively affects large plants on plantations but not in natural forests. Large plants increased slightly with increasing climatic water availability in the natural forest but decreased in plantation, whereas soil fertility inhibited large plants in plantation only. This study highlights the extended generality of the big-sized trees hypothesis, scaling theory, and the global importance of big-sized tree in arid natural forests and plantations.
ABSTRACT
Meteorological factors have been confirmed to affect the COVID-19 transmission, but current studied conclusions varied greatly. The underlying causes of the variance remain unclear. Here, we proposed two scientific questions: (1) whether meteorological factors have a consistent influence on virus transmission after combining all the data from the studies; (2) whether the impact of meteorological factors on the COVID-19 transmission can be influenced by season, geospatial scale and latitude. We employed a meta-analysis to address these two questions using results from 2813 published articles. Our results showed that, the influence of meteorological factors on the newly-confirmed COVID-19 cases varied greatly among existing studies, and no consistent conclusion can be drawn. After grouping outbreak time into cold and warm seasons, we found daily maximum and daily minimum temperatures have significant positive influences on the newly-confirmed COVID-19 cases in cold season, while significant negative influences in warm season. After dividing the scope of the outbreak into national and urban scales, relative humidity significantly inhibited the COVID-19 transmission at the national scale, but no effect on the urban scale. The negative impact of relative humidity, and the positive impacts of maximum temperatures and wind speed on the newly-confirmed COVID-19 cases increased with latitude. The relationship of maximum and minimum temperatures with the newly-confirmed COVID-19 cases were more susceptible to season, while relative humidity's relationship was more affected by latitude and geospatial scale. Our results suggested that relationship between meteorological factors and the COVID-19 transmission can be affected by season, geospatial scale and latitude. A rise in temperature would promote virus transmission in cold seasons. We suggested that the formulation and implementation of epidemic prevention and control should mainly refer to studies at the urban scale. The control measures should be developed according to local meteorological properties for individual city.
