Intra-annual stem radial growth of Qinghai spruce and its environmental drivers in the Qilian Mountains, northwestern China

Tree stem radial growth could be used to estimate forest productivity, which plays a dominant role in the carbon sink of terrestrial ecosystems. However, it is still obscure how intra-annual stem radial growth is regulated by environmental variables. Here, we monitored Qinghai spruce stem radial growth over seven years and analyzed the environmental drivers of the intra-annual stem radial changes in the Qilian Mountains at low (2700 m) and high altitudes (3200 m). We found that stem radial growth initiated when the daily mean minimum air temperature reached 1.6oC, while the cessation of stem growth was unrelated to temperatures and water conditions. Initiations of stem growth at 2700 m were significantly earlier than that at 3200 m. Maximum growth rates were observed before the summer solstice at low altitude, whereas at high altitude, the majority of them occurred after the summer solstice. Most variability in annual stem increment (AI) can be explained by the rate (Rm) than by the duration of stem growth (∆t), and 78.9 % and 69.6 % of the variability in AI were attributable to Rm for the lower and upper site, respectively. Structural equation modeling revealed that precipitation (P) could both directly positively influence stem radial increment (SRI) and indirectly positively influence SRI through influencing relative humidity (RH), but the positive effect of P on SRI was higher at low altitude than at high altitude. Daily minimum air temperature (Tmin) was also the main direct diver of SRI, and the positive effect of Tmin on SRI was higher at high altitude than at low altitude. Considering the trends in climate warming and humidification over the past decades, climate changes would result in earlier initiation of Qinghai spruce stem growth and promote the growth through positive response to increased precipitation in low altitude and through elevated temperature in high altitude, respectively.

Microbial community structure and its driving mechanisms in the Hangbu estuary of Chaohu Lake under different sedimentary areas

Estuaries are known for their high ecological diversity and biological productivity. Sediment microorganisms, as crucial components of estuarine ecosystems, play a pivotal role in reflecting the intricate and dynamic ecological niches. However, our research on microbial community characteristics in estuarine ecosystems under different sedimentary types remains limited. In this study, we collected a total of 27 samples from three sampling sites at Hangbu estuary in Chaohu Lake, and three sedimentary areas were classified based on the overlying water flow conditions and sediment particle properties to elucidate their microbial community structure, environmental drivers, assembly processes, and co-occurrence network characteristics. Our results showed significant differences in microbial community composition and diversity among three sedimentary areas. Redundancy analysis indicated that the differences in microbial community composition at the OTU level among the three sedimentary areas were mainly determined by nitrate-nitrogen, temperature, and water content. Phylogenetic bin-based null model analysis revealed that temperature was a key factor influencing deterministic processes among the three sedimentary areas, while stochastic processes predominantly governed the assembly of microbial communities. In addition, co-occurrence network analysis demonstrated that the network in the hydraulically driven sedimentary area of the lake, consisting mainly of medium and fine silt, had the highest complexity, stability, and cohesion, but was missing potential keystone taxa. The remaining two sedimentary areas had 5 and 8 potential keystone taxa, respectively. Overall, our study proposes the delineation of sedimentary types and comprehensively elucidates the microbial community characteristics under different sedimentary areas, providing a new perspective for studying sediment microbial community structure and helping future scholars systematically study ecological dynamics in estuaries.

N2O emission factors for cattle urine: effect of patch characteristics and environmental drivers

Urine patches from grazing cattle are hotspots of nitrous oxide (N2O) emissions. The default IPCC emission factor for urine patches (EFurine) is 0.77% for wet climates and 0.32% for dry climates. However, literature reports a considerable range of cattle urine EF values and urine characteristics used in experimental studies, revealing contrary results on the effects of urine patch characteristics and seasonal pattern. Therefore, we examined N2O emissions and corresponding EFurine values in relation to urine patch characteristics (urine N concentration, urine volume, patch area, urine composition) and environmental drivers (precipitation, water filled pore space, soil temperature). Ten artificial urine application experiments were performed from July 2020 to June 2022 on a pasture located in Eastern Switzerland. Urine N concentration, patch area, volume and urine N composition showed no significant effects on the EFurine value (p > 0.05). EFurine varied, however, strongly over time (0.17-2.05%). A large part of the variation could be predicted either by cumulative precipitation 20 days after urine application using a second order polynomial model (Adj. R2 = 0.60) or average WFPS 30 days after urine application using a linear model (Adj. R2 = 0.45). The derived precipitation model was used to simulate EFurine weekly over the last 20 years showing no significant differences between the seasons of a year. The resulting overall average EFurine was 0.67%. More field studies are needed across sites/regions differing in climate and soil properties to implement a country-specific EF3 for Switzerland and to improve the quantification of N2O emissions at the national scales.

Algal community structure prediction by machine learning

The algal community structure is vital for aquatic management. However, the complicated environmental and biological processes make modeling challenging. To cope with this difficulty, we investigated using random forests (RF) to predict phytoplankton community shifting based on multi-source environmental factors (including physicochemical, hydrological, and meteorological variables). The RF models robustly predicted the algal communities composed by 13 major classes (Bray-Curtis dissimilarity = 9.2 ± 7.0%, validation NRMSE mostly <10%), with accurate simulations to the total biomass (validation R² > 0.74) in Norway's largest lake, Lake Mjosa. The importance analysis showed that the hydro-meteorological variables (Standardized MSE and Node Purity mostly >0.5) were the most influential factors in regulating the phytoplankton. Furthermore, an in-depth ecological interpretation uncovered the interactive stress-response effect on the algal community learned by the RF models. The interpretation results disclosed that the environmental drivers (i.e., temperature, lake inflow, and nutrients) can jointly pose strong influence on the algal community shifts. This study highlighted the power of machine learning in predicting complex algal community structures and provided insights into the model interpretability.

Soil antibiotic abatement associates with the manipulation of soil microbiome via long-term fertilizer application

The effects of different fertilization on microbial communities and resistome in agricultural soils with a history of fresh manure application remains largely unclear. Here, soil antibiotic resistance genes (ARGs), mobile genetic elements (MGEs) and microbial communities were deciphered using metagenomics approach from a long-term field experiment with different fertilizer inputs. A total of 541 ARG subtypes were identified, with Multidrug, Macrolides-Lincosamides-Streptogramins (MLS), and Bacitracin resistance genes as the most universal ARG types. The abundance of ARGs detected in manure (2.52 ARGs/16 S rRNA) treated soils was higher than chemical fertilizer (2.42 ARGs/16 S rRNA) or compost (2.37 ARGs/16 S rRNA) amended soils. The higher abundance of MGEs and the enrichment of Proteobacteria were observed in manure treated soils than in chemical fertilizer or compost amended soils. Proteobacter and Actinobacter were recognized as the main potential hosts of ARGs revealed by network analysis. Further soil pH was identified as the key driver in determining the composition of both microbial community and resistome. The present study investigated the mechanisms driving the microbial community, MGEs and ARG profiles of long-term fertilized soils with ARGs contamination, and our findings could support strategies to manage the dissemination of soil ARGs.

Effects of environmental factors on the distribution of microbial communities across soils and lake sediments in the Hoh Xil Nature Reserve of the Qinghai-Tibetan Plateau

Comparison of microbial community diversity and composition of terrestrial and aquatic ecosystems in undisturbed regions could expand our understanding on the mechanisms of microbial community assembly and ecosystem responses to environmental change. This study investigated the spatial distribution of bacterial community diversity and composition in the lakeshore soils and lake sediments from one of the best preserved nature reserves, Hoh Xil on the Qinghai-Tibetan Plateau, and explored the corresponding environmental drivers. A total of 36 sediment and soil samples were collected from six alpine lakes and the corresponding shore zones, and their bacterial community structure was identified by high-throughput 16S rRNA gene sequencing. Significant difference (p < 0.05) in diversity and composition of bacterial communities between the soils and sediments was observed. Heterogeneous selection played a dominant role in shaping the spatial variations of bacterial communities between the soils and sediments. Results of canonical correspondence analysis showed that the difference in composition of bacterial communities at OTU level between the soils and sediments was mainly determined by the mean annual temperature, salinity, and contents of total organic carbon and total nitrogen. Structural equation modeling revealed that salinity played a significantly direct role in soil bacterial composition, while mean annual temperature indirectly affected the bacterial composition mainly through changing soil salinity. In contrast, the sediment bacterial composition was directly influenced primarily by the contents of total organic carbon and total nitrogen, while pH also had an important indirect effect on sediment bacterial composition. These results shed light on the distribution patterns of bacterial communities between lakeshore soils and lake sediments in high-altitude permafrost regions, and the major ecological processes and environmental drivers that shaped their bacterial communities, and provide insight into the mechanisms underlying microbial community assembly in such regions.

Molecular biogeography of planktonic and benthic diatoms in the Yangtze River

BACKGROUND

Diatoms are of great significance to primary productivity in oceans, yet little is known about their biogeographic distribution in oligotrophic rivers.

RESULTS

With the help of metabarcoding analysis of 279 samples from the Yangtze River, we provided the first integral biogeographic pattern of planktonic and benthic diatoms over a 6030 km continuum along the world's third largest river. Our study revealed spatial dissimilarity of diatoms under varying landforms, including plateau, mountain, foothill, basin, foothill-mountain, and plain regions, from the river source to the estuary. Environmental drivers of diatom communities were interpreted in terms of photosynthetically active radiation, temperature, channel slope and nutrients, and human interference. Typical benthic diatoms, such as Pinnularia, Paralia, and Aulacoseira, experienced considerable reduction in relative abundance downstream of the Three Gorges Dam and the Xiluodu Dam, two of the world's largest dams.

CONCLUSIONS

Our study revealed that benthic diatoms are of particular significance in characterizing motile guild in riverine environments, which provides insights into diatom biogeography and biogeochemical cycles in large river ecosystems.

Construction sites as an important driver of dengue transmission: implications for disease control

BACKGROUND

In 2013 and 2014, Singapore experienced its worst dengue outbreak known-to-date. Mosquito breeding in construction sites stood out as a probable risk factor due to its association with major dengue clusters in both years. We, therefore, investigated the contribution of construction sites to dengue transmission in Singapore, highlighting three case studies of large construction site-associated dengue clusters recorded during 2013-16.

METHODS

The study included two components; a statistical analysis of cluster records from 2013 to 2016, and case studies of three biggest construction site-associated clusters. We explored the odds of construction site-associated clusters growing into major clusters and determined whether clusters seeded in construction sites demonstrated a higher tendency to expand into major clusters. DENV strains obtained from dengue patients residing in three major clusters were genotyped to determine whether the same strains expanded into the surroundings of construction sites.

RESULTS

Despite less than 5% of total recorded clusters being construction site-associated, the odds of such clusters expanding into major clusters were 17.4 (2013), 9.2 (2014), 3.3 (2015) and 4.3 (2016) times higher than non-construction site clusters. Aedes premise index and average larvae count per habitat were also higher in construction sites than residential premises during the study period. The majority of cases in clusters associated with construction sites were residents living in the surroundings. Virus genotype data from three case study sites revealed a transmission link between the construction sites and the surrounding residential areas.

CONCLUSIONS

Significantly high case burden and the probability of cluster expansion due to virus spill-over into surrounding areas suggested that construction sites play an important role as a driver of sustained dengue transmission. Our results emphasise that the management of construction-site associated dengue clusters should not be limited to the implicated construction sites, but be extended to the surrounding premises to prevent further transmission.

Ground beetles in city forests: does urbanization predict a personality trait?

BACKGROUND

Urbanization leads to substantial changes in natural habitats with profound effects on wildlife. Understanding behavioural responses to such environmental change is essential for identifying which organisms may adapt, as behaviour is often the first response to altered conditions. Individuals in more urbanized habitats may be expected to be more exploratory and bolder than their conspecifics in less urbanized habitats as they may be better able to cope with novel challenges.

METHODS

In a two-year field study we tested ground beetles from differently urbanized forests for their exploratory behaviour (in a novel environment) and their risk-taking (death-feigning). In total, we tested ca. 3,000 individuals of four forest-dwelling ground beetle species from eight within-city forest patches. In the second year, we also transferred ca. 800 tested individuals of two species to the laboratory to test for consistent behavioural differences (i.e. personality differences) under standardised conditions.

RESULTS

Individuals were generally more exploratory in more urbanized than in less urbanized areas but only in one year of the study. Exploratory behaviour was not predicted by population density but increased with temperature or showed a temperature optimum. Exploration was consistent over time and individuals that were more exploratory also took higher risks.

DISCUSSION

We demonstrated that species which are generally less directly exposed to human activities (e.g., most invertebrates) show behavioural responses to urbanization. Effects of urbanization were year-dependent, suggesting that other environmental conditions interacted with effects of urbanization on beetle behaviour. Furthermore, our results indicate that different personality compositions might cause behavioural differences among populations living in differently urbanized habitats.

Spatial variations in annual cycles of body-size spectra of planktonic ciliates and their environmental drivers in marine ecosystems

Body-size spectra has proved to be a useful taxon-free resolution to summarize a community structure for bioassessment. The spatial variations in annual cycles of body-size spectra of planktonic ciliates and their environmental drivers were studied based on an annual dataset. Samples were biweekly collected at five stations in a bay of the Yellow Sea, northern China during a 1-year cycle. Based on a multivariate approach, the second-stage analysis, it was shown that the annual cycles of the body-size spectra were significantly different among five sampling stations. Correlation analysis demonstrated that the spatial variations in the body-size spectra were significantly related to changes of environmental conditions, especially dissolved nitrogen, alone or in combination with salinity and dissolve oxygen. Based on results, it is suggested that the nutrients may be the environmental drivers to shape the spatial variations in annual cycles of planktonic ciliates in terms of body-size spectra in marine ecosystems.

An approach to analyzing environmental drivers to spatial variations in annual distribution of periphytic protozoa in coastal ecosystems

The environmental drivers to the spatial variation in annual distribution were studied based on an annual dataset of periphytic protozoa using multivariate approaches. Samples were monthly collected at four stations within a pollution gradient in coastal waters of the Yellow Sea, northern China during a 1-year period. The second-stage (2STAGE) analyses showed that the internal patterns of the annual distribution were changed along the pollution gradient in terms of abundance. The dominant species represented different succession dynamics among four sampling stations during a 1-year cycle. Best matching analysis demonstrated that the spatial variations in annual distribution of the protozoa were significantly correlated with ammonium nitrogen (NH4-N), alone or in combination with salinity and dissolved oxygen (DO). Based on the results, we suggest that the nutrients, salinity and DO may be the main drivers to shape the spatial variations in annual distribution of periphytic protozoa.