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The ecological drivers of soil biodiversity in the Southern Hemisphere remain underexplored. Here, in a continental survey comprising 647 sites, across 58 degrees of latitude between tropical Australia and Antarctica, we evaluated the major ecological patterns in soil biodiversity and relative abundance of ecological clusters within a co-occurrence network of soil bacteria, archaea and eukaryotes. Six major ecological clusters (modules) of co-occurring soil taxa were identified. These clusters exhibited strong shifts in their relative abundances with increasing distance from the equator. Temperature was the major environmental driver of the relative abundance of ecological clusters when Australia and Antarctica are analyzed together. Temperature, aridity, soil properties and vegetation types were the major drivers of the relative abundance of different ecological clusters within Australia. Our data supports significant reductions in the diversity of bacteria, archaea and eukaryotes in Antarctica vs. Australia linked to strong reductions in temperature. However, we only detected small latitudinal variations in soil biodiversity within Australia. Different environmental drivers regulate the diversity of soil archaea (temperature and soil carbon), bacteria (aridity, vegetation attributes and pH) and eukaryotes (vegetation type and soil carbon) across Australia. Together, our findings provide new insights into the mechanisms driving soil biodiversity in the Southern Hemisphere.

Aims We examined the importance of litter quality and microclimate on early-stage litter mass loss, analysed the importance of interactions among environmental factors in determining key decomposition parameters and compared the variation in decomposition rates in vegetation types and sites with similar climate. Methods Following the Tea-Bag Index approach, 464 tea-bags were incubated in the soil in 79 sites, distributed across Italy, which included six vegetation types and a broad range of microclimatic conditions. Results Litter type exerted a stronger control on mass loss compared to climatic factors. The effects of soil moisture were not the same for high and lower quality litter. In addition, the effects of temperature on the decomposition rate depended on soil moisture. The stabilization factor was strongly temperature-dependent, but the influence of temperature differed among vegetation types: those dominated by small-size plants showed a strong decrease in the potential amount of plant material entering into the soil stock under warmer temperatures. The lowest variation in decomposition rate was found in sites characterised by low temperatures, and, among the vegetation types, in alpine snowbeds. Conclusions The role of litter quality and of the interactions among environmental conditions can potentially determine significant shifts in the expected patterns of ecosystem carbon fluxes.

The views expressed in this paper result from the exchange of ideas among its authors during a workshop organized by the Vegetation Classification Committee of the International Association for Vegetation Science (IAVS), held in Rome in April 2013, and subsequent discussions. The International Association for Vegetation Science (IAVS) supported the workshop leading to this contribution. Additional funding to M.D.C. came from Masaryk University and from a fellowship of the Spanish Ministry of Economy and Competitiveness (RYC‐2012‐11109). M.C. and L.T. were supported by the Czech Science Foundation (P505/11/0732). R.G. was supported by REMEDINAL3‐CM (S2013/MAE‐2719), B.C. by the Bolyai grant of the Hungarian Academy of Sciences, and L.M. acknowledges the Iluka Chair (University of Western Australia).

Knowledge of the soil organic carbon components and enzyme activities during long‐term natural vegetation restoration is essential for managing the restoration of vegetation. In this study, the variations of soil organic carbon components (i.e., soil organic carbon (SOC), microbial biomass carbon (MBC), easily oxidized carbon (EOC), particulate organic carbon (POC)) and enzyme activities (i.e., amylase, catalase, urease, and sucrase) were measured in four vegetation types: control (grasslands, GL), forest (Xanthoceras sorbifolia, XS), and shrublands (Hippophae rhamnoides, HR; Caragana korshinskii, CK). We found that vegetation types significantly affect soil organic carbon components and enzyme activities. The SOC content of the XS plot is higher than HR, CK, and GL by 88.43%, 117.09%, and 37.53% at the 0–20 cm layer; the soil SOC content of the XS plot is higher than HR and CK by 27.04% and 26.87%, and lower than GL 12.90% at the 20–40 cm layer. The highest POC and urease were observed in the XS plot at a depth of 0–20 cm, that is, 1.32 g/kg and 98.51 mg/kg, respectively. The highest EOC, amylase, and sucrase were observed in GL at a depth of 0–20 cm, that is, 5.44 g/kg, 39.23, and 607.62 mg/g. On the vertical section of the soil, the SOC fractions and the enzyme activities were greater in the upper layer than in the lower layer for each vegetation type except for MBC and catalase activity. Correlation analysis demonstrated that the SOC and POC content significantly influenced urease and sucrase activities and that MBC significantly influenced catalase activity. These results provide important information about SOC fractions and enzyme activities resulting from vegetation types in the Loess Plateau and also supplement our understanding of soil C sequestration in vegetation restoration. On the vertical section of the soil, the SOC fractions and the enzyme activities were greater in the upper layer than in the lower layer for each vegetation type except for MBC and catalase activity. Correlation analysis demonstrated that the SOC and POC content significantly influenced urease and sucrase activities and that MBC significantly influenced catalase activity. These results provide important information about SOC fractions and enzyme activities resulting from vegetation types in the Loess Plateau and also supplement our understanding of soil C sequestration in vegetation restoration.

Land surface temperature (LST) is a key variable in surface-atmosphere energy and water exchanges. The main goals of this study are to (i) evaluate the LST of the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim and ERA5 reanalyses over Iberian Peninsula using the Satellite Application Facility on Land Surface Analysis (LSA-SAF) product and to (ii) understand the main drivers of the LST errors in the reanalysis. Simulations with the ECMWF land-surface model in offline mode (uncoupled) were carried out over the Iberian Peninsula and compared with the reanalysis data. Several sensitivity simulations were performed in a confined domain centered in Southern Portugal to investigate potential sources of the LST errors. The Copernicus Global Land Service (CGLS) fraction of green vegetation cover (FCover) and the European Space Agency’s Climate Change Initiative (ESA-CCI) Land Cover dataset were explored. We found a general underestimation of daytime LST and slightly overestimation at night-time. The results indicate that there is still room for improvement in the simulation of LST in ECMWF products. Still, ERA5 presents an overall higher quality product in relation to ERA-Interim. Our analysis suggested a relation between the large daytime cold bias and vegetation cover differences between (ERA5 and CGLS FCocver) with a correlation of −0.45. The replacement of the low and high vegetation cover by those of ESA-CCI provided an overall reduction of the large Tmax biases during summer. The increased vertical resolution of the soil at the surface, has a positive impact, but much smaller when compared with the vegetation changes. The sensitivity of the vegetation density parameter, that currently depends on the vegetation type, provided further proof for a needed revision of the vegetation in the model, as there is a reasonable correlation between this parameter and the Tmax mean errors when using the ESA-CCI vegetation cover (while the same correlation cannot be reproduced with the original model vegetation). Our results support the hypothesis that vegetation cover is one of the main drivers of the LST summertime cold bias in ERA5 over Iberian Peninsula.

• Plant nutrient-acquisition strategies drive soil processes and vegetation performance, but their effect on the soil microbiome remains poorly understood. This knowledge is important to predict the shifts in microbial diversity and functions due to increasing changes in vegetation traits under global change. • Here we documented the topsoil microbiomes of 145 boreal and temperate terrestrial sites in the Baltic region that broadly differed in vegetation type and nutritional traits, such as mycorrhizal types and symbiotic nitrogen-fixation. • We found that sites dominated by arbuscular mycorrhizal (AM) vegetation harbor relatively more AM fungi, bacteria, fungal saprotrophs, and pathogens in the topsoil compared with sites dominated by ectomycorrhizal (EM) plants. These differences in microbiome composition reflect the rapid nutrient cycling and negative plant–soil feedback in AM soils. Lower fungal diversity and bacteria : fungi ratios in EM-dominated habitats are driven by monodominance of woody vegetation as well as soil acidification by EM fungi, which are associated with greater diversity and relative abundance of carbohydrate-active enzymes. • Our study suggests that shifts in vegetation related to global change and land use may strongly alter the topsoil microbiome structure and function.

1. Dispersal is an essential component of plant life, especially under the current threats of anthropogenic habitat fragmentation and climate change. For many wetland species, water is a key dispersal vector, as it can presumably disperse seeds long distances and towards suitable sites for establishment. Seed dispersal distance is affected by stream characteristics and seed traits. Yet, the effect of relevant seed traits, such as size, remains largely unknown. 2. Here, we report on an experimental field study examining the effect of seed size on dispersal distance in lowland streams. We released cork seed mimics of different sizes in four Dutch lowland streams in restored and channelized sections. After 24 hr, we recorded their entrapment location, entrapment mechanism, and the vegetation type in which they were caught. 3. Large seeds generally dispersed over longer distances than smaller seeds. This effect of seed size is likely caused by the different entrapment mechanisms— net trapping, surface tension, and wake trapping—which were highly correlated with seed size. Especially net trapping was responsible for the capture of a large proportion of small seed mimics in vegetation such as aquatic and riparian grasses, starwort, and reed. Due to the prevalent occurrence of these vegetation types in lowland streams, particularly during summer, smaller seeds are more likely to become entrapped and, hence, disperse less far. Our analysis on existing seed data reveals that water-dispersed riparian plants have relatively large seeds and are thereby evolutionarily adapted to long-distance dispersal. Furthermore, our results indicate that median dispersal distances are 0.02-1.8 km (99-percentile <8.5 km) in lowland streams in summer. In winter, less vegetation is present in and surrounding the streams, which leads to median dispersal distances of 0.12-14.2 km (99-percentile <65 km). 4. Synthesis. This study demonstrates that (a) large seeds generally disperse further than smaller seeds in lowland steams and (b) distances depend strongly on stream vegetation. This information should inform future restoration, for instance, by planning efforts to coincide with times or conditions of open water which are more favourable for the dispersal of target plant species— especially those with small seeds (<10 mm).

The three-river headwater region (TRHR) supplies the Yangtze, Yellow, and Lantsang rivers, and its ecological environment is fragile, hence it is important to study the surface vegetation cover status of the TRHR to facilitate its ecological conservation. The normalized difference vegetation index (NDVI) can reflect the cover status of surface vegetation. The aims of this study are to quantify the spatial heterogeneity of the NDVI, identify the main driving factors influencing the NDVI, and explore the interaction between these factors. To this end, we used the global inventory modeling and mapping studies (GIMMS)-NDVI data from the TRHR from 1982 to 2015 and included eight natural factors (namely slope, aspect, elevation, soil type, vegetation type, landform type, annual mean temperature, and annual precipitation) and three anthropogenic factors (gross domestic product (GDP), population density, and land use type), which we subjected to linear regression analysis, the Mann-Kendall statistical test, and moving t-test to analyze the spatial and temporal variability of the NDVI in the TRHR over 34 years, using a geographical detector model. Our results showed that the NDVI distribution of the TRHR was high in the southeast and low in the northwest. The change pattern exhibited an increasing trend in the west and north and a decreasing trend in the center and south; overall, the mean NDVI value from 1982 to 2015 has increased. Annual precipitation was the most important factor influencing the NDVI changes in the TRHR, and factors, such as annual mean temperature, vegetation type, and elevation, also explained the vegetation coverage status well. The influence of natural factors was generally stronger than that of anthropogenic factors. The NDVI factors had a synergistic effect, exhibiting mutual enhancement and nonlinear enhancement relationships. The results of this study provide insights into the ecological conservation of the TRHR and the ecological security and development of the middle and lower reaches.

Vegetation significantly affects the soil properties and runoff processes of gully head systems, thereby affecting their development. However, the mechanisms underlying the effects of vegetation on gully headcut erosion remain unclear. To explore these mechanisms, a series of simulation experiments were carried out on plots with four types of vegetation and bare land (BL). The results revealed that vegetation reduces the runoff velocity in the upstream area (Vup), gully head brink (Vbrink), and gully bed (Vbed) areas by 15%–70%, 3%–54%, and 1%–30%, respectively, and that vegetation type impacts Vup, with no obvious impacts on Vbrink, the jet flow velocity (Vjet) or Vbed. Vegetation reduced the jet flow shear stress (τjet) under low inflow discharge, but under high inflow discharge, it increased τjet. Different vegetation types exhibited different effects on the increase in the Darcy–Weisbach friction factor (f) and Manning roughness coefficient (n) in the upstream area, whereas the effect of vegetation on the f and n value of the gully bed was not obvious. Vegetation reduced the gully head retreat length. Compared with BL, vegetation reduced the rate of soil loss by 31%–95%. Vegetation significantly and directly affects soil characteristics, hydrodynamic parameters, and gully head morphology. The gully head morphology significantly and directly influences the soil loss rate, which ultimately affected the length of gully head retreat. These findings contribute to a deeper understanding of the role of vegetation in gully headcut erosion, offering a scientific foundation for the implementation of preventive measures against such erosion. Key Points Vegetation reduced the jet flow shear stress (τjet) under low inflow discharge, but under high inflow discharge, it increased τjet Vegetation significantly and directly affects soil characteristics, hydrodynamic parameters and gully head morphology The gully head morphology directly affects the soil loss rate, and the soil loss rate ultimately affects the length of gully head retreat

ContextThe role of landscape diversity and structure is crucial for maintaining biodiversity. Both landscape diversity and structure have often been analysed on one thematic layer, focusing on Shannon diversity. The application of compositional diversity, however, has received little attention yet.ObjectivesOur main goal was to introduce a novel framework to assess both landscape compositional diversity and structure in one coherent framework. Moreover, we intended to demonstrate the significance of the use of a neutral model for landscape assessments.MethodsBoth entire Hungary and nine of its regions were used as study areas. Juhász-Nagy’s information theory-based functions, i.e. “compositional diversity” and “associatum”, were introduced and applied in landscape context. Potential and actual landscape characteristics were compared by analysing a probabilistic representation of potential natural vegetation (multiple PNV, MPNV) and actual vegetation (AV), treating MPNV as a neutral model.ResultsA significant difference was found between the MPNV- and AV-based, maximal compositional diversity estimates. MPNV-based maximal compositional diversity was higher and the maximum appeared at a finer spatial scale. The differences were more prominent in human-modified regions. Associatum implied the spatial aggregation of both MPNV and AV. Fragmentation of AV was indicated by larger units carrying maximal compositional diversity and maximal associatum values.ConclusionsApplying the multiscale Juhász-Nagy’s functions to landscape composition allowed more precise characterization of the landscape state than traditional Shannon diversity. Our results underline, that increasingly transformed landscapes host decreasing complexity of vegetation type combinations and increasing grain that carries the richest information on landscape vegetation patterns.