Species richness is more important for ecosystem functioning than species turnover along an elevational gradient.

Many experiments have shown that biodiversity enhances ecosystem functioning. However, we have little understanding of how environmental heterogeneity shapes the effect of diversity on ecosystem functioning and to what extent this diversity effect is mediated by variation in species richness or species turnover. This knowledge is crucial to scaling up the results of experiments from local to regional scales. Here we quantify the diversity effect and its components-that is, the contributions of variation in species richness and species turnover-for 22 ecosystem functions of microorganisms, plants and animals across 13 major ecosystem types on Mt Kilimanjaro, Tanzania. Environmental heterogeneity across ecosystem types on average increased the diversity effect from explaining 49% to 72% of the variation in ecosystem functions. In contrast to our expectation, the diversity effect was more strongly mediated by variation in species richness than by species turnover. Our findings reveal that environmental heterogeneity strengthens the relationship between biodiversity and ecosystem functioning and that species richness is a stronger driver of ecosystem functioning than species turnover. Based on a broad range of taxa and ecosystem functions in a non-experimental system, these results are in line with predictions from biodiversity experiments and emphasize that conserving biodiversity is essential for maintaining ecosystem functioning.

Interaction of livestock grazing and rainfall manipulation enhances herbaceous species diversity and aboveground biomass in a humid savanna.

Understanding of the interaction of livestock grazing and rainfall variability may aid in predicting the patterns of herbaceous species diversity and biomass production. We manipulated the amount of ambient rainfall received in grazed and ungrazed savanna in Lambwe Valley-Kenya. The combined influence of livestock grazing and rainfall on soil moisture, herbaceous species diversity, and aboveground biomass patterns was assessed. We used the number of species (S), Margalef's richness index (Dmg), Shannon index of diversity (H), and Pileou's index of evenness (J) to analyze the herbaceous community structure. S, Dmg, H and J were higher under grazing whereas volumetric soil water contents (VWC) and aboveground biomass (AGB) decreased with grazing. Decreasing (50%) or increasing (150%) the ambient rainfall by 50% lowered species richness and diversity. Seasonality in rainfall influenced the variation in VWC, S, Dmg, H, and AGB but not J (p = 0.43). Overall, Dmg declined with increasing VWC. However, the AGB and Dmg mediated the response of H and J to the changes in VWC. The highest H occurred at AGB range of 400-800 g m-2. We attribute the lower diversity in the ungrazed plots to the dominance (relative abundance > 70%) of Hyparrhenia fillipendulla (Hochst) Stapf. and Brachiaria decumbens Stapf. Grazing exclusion, which controls AGB, hindered the coexistence among species due to the competitive advantage in resource utilization by the more dominant species. Our findings highlight the implication of livestock grazing and rainfall variability in maintaining higher diversity and aboveground biomass production in the herbaceous layer community for sustainable ecosystem management.

Climate-land-use interactions shape tropical mountain biodiversity and ecosystem functions.

Agriculture and the exploitation of natural resources have transformed tropical mountain ecosystems across the world, and the consequences of these transformations for biodiversity and ecosystem functioning are largely unknown1-3. Conclusions that are derived from studies in non-mountainous areas are not suitable for predicting the effects of land-use changes on tropical mountains because the climatic environment rapidly changes with elevation, which may mitigate or amplify the effects of land use4,5. It is of key importance to understand how the interplay of climate and land use constrains biodiversity and ecosystem functions to determine the consequences of global change for mountain ecosystems. Here we show that the interacting effects of climate and land use reshape elevational trends in biodiversity and ecosystem functions on Africa's largest mountain, Mount Kilimanjaro (Tanzania). We find that increasing land-use intensity causes larger losses of plant and animal species richness in the arid lowlands than in humid submontane and montane zones. Increases in land-use intensity are associated with significant changes in the composition of plant, animal and microorganism communities; stronger modifications of plant and animal communities occur in arid and humid ecosystems, respectively. Temperature, precipitation and land use jointly modulate soil properties, nutrient turnover, greenhouse gas emissions, plant biomass and productivity, as well as animal interactions. Our data suggest that the response of ecosystem functions to land-use intensity depends strongly on climate; more-severe changes in ecosystem functioning occur in the arid lowlands and the cold montane zone. Interactions between climate and land use explained-on average-54% of the variation in species richness, species composition and ecosystem functions, whereas only 30% of variation was related to single drivers. Our study reveals that climate can modulate the effects of land use on biodiversity and ecosystem functioning, and points to a lowered resistance of ecosystems in climatically challenging environments to ongoing land-use changes in tropical mountainous regions.

Environmental drivers of spatial patterns of topsoil nitrogen and phosphorus under monsoon conditions in a complex terrain of South Korea.

Nitrogen (N) and phosphorus (P) in topsoils are critical for plant nutrition. Relatively little is known about the spatial patterns of N and P in the organic layer of mountainous landscapes. Therefore, the spatial distributions of N and P in both the organic layer and the A horizon were analyzed using a light detection and ranging (LiDAR) digital elevation model and vegetation metrics. The objective of the study was to analyze the effect of vegetation and topography on the spatial patterns of N and P in a small watershed covered by forest in South Korea. Soil samples were collected using the conditioned latin hypercube method. LiDAR vegetation metrics, the normalized difference vegetation index (NDVI), and terrain parameters were derived as predictors. Spatial explicit predictions of N/P ratios were obtained using a random forest with uncertainty analysis. We tested different strategies of model validation (repeated 2-fold to 20-fold and leave-one-out cross validation). Repeated 10-fold cross validation was selected for model validation due to the comparatively high accuracy and low variance of prediction. Surface curvature was the best predictor of P contents in the organic layer and in the A horizon, while LiDAR vegetation metrics and NDVI were important predictors of N in the organic layer. N/P ratios increased with surface curvature and were higher on the convex upper slope than on the concave lower slope. This was due to P enrichment of the soil on the lower slope and a more even spatial distribution of N. Our digital soil maps showed that the topsoils on the upper slopes contained relatively little P. These findings are critical for understanding N and P dynamics in mountainous ecosystems.

Transport of sulfonamide antibiotics in crop fields during monsoon season.

Previous studies have documented the occurrence of veterinary sulfonamide antibiotics in groundwater and rivers located far from pollution sources, although their transport and fate is relatively unknown. In mountainous agricultural fields, the transport behaviour can be influenced by climate, slope and physico-chemical properties of the sulfonamides. The objective of this research is to describe the transport behaviour of three sulfonamide antibiotics (sulfamethoxazole, sulfadimethoxine and sulfamethazine) in sloped agricultural fields located in the Haean catchment, South Korea. During dry and monsoon seasons, a solute transport experiment was conducted in two typical sandy loam agricultural fields after application of antibiotics and potassium bromide as conservative tracers. Field measurement and modelling revealed that frequency and amount of runoff generation indicate a relation between slope and rain intensity during monsoon season. Since the steepness of slope influenced partitioning of precipitation between runoff and subsurface flow, higher loss of sulfonamide antibiotics and bromide by runoff was observed at the steeper sloped field. Bromide on topsoil rapidly infiltrated at high infiltration rates. On the contrary, the sulfonamides were relatively retarded in the upper soil layer due to adsorption onto soil particles. Presence of furrows and ridges affected the distribution of sulfonamide antibiotics in the subsurface due to gradient from wetter furrows to drier ridges induced by topography. Modelling results with HydroGeoSphere matched with background studies that describe physico-chemical properties of the sulfonamides interaction between soil and the antibiotic group, solute transport through vadose zone and runoff generation by storm events.

Effect of pH and soil structure on transport of sulfonamide antibiotics in agricultural soils.

We investigated the effect of solution pH and soil structure on transport of sulfonamide antibiotics (sulfamethoxazole, sulfadimethoxine and sulfamethazine) in combination with batch sorption tests and column experiments. Sorption isotherms properly conformed to Freundlich model, and sorption potential of the antibiotics is as follows; sulfadimethoxine > sulfamethoxazole > sulfamethazine. Decreasing pH values led to increased sorption potential of the antibiotics on soil material in pH range of 4.0-8.0. This likely resulted from abundance of neutral and positive-charged sulfonamides species at low pH, which electrostatically bind to sorption sites on soil surface. Due to destruction of macropore channels, lower hydraulic conductivities of mobile zone were estimated in the disturbed soil columns than in the undisturbed soil columns, and eventually led to lower mobility of the antibiotics in disturbed column. The results suggest that knowledge of soil structure and solution condition is required to predict fate and distribution of sulfonamide antibiotics in environmental matrix.

Sulfadimethoxine transport in soil columns in relation to sorbable and non-sorbable tracers.

In this study, miscible displacement experiment and batch sorption experiments were performed with sulfadimethoxine, dye tracer, Brilliant Blue FCF (BB) and a conservative tracer (bromide) to depict, analyse and interpret transport paths of sulfadimethoxine in undisturbed and disturbed soil columns. Batch sorption experiment revealed that sorption potential increased in the order: Brilliant Blue FCF > sulfadimethoxine > bromide. The horizontal spatial patterns of sulfadimethoxine and the tracers were analysed in each depth, and selective samples were taken in horizontal cross-section. Non-adsorbable and conservative tracer, bromide spread more widely into longitudinal and horizontal direction than sulfadimethoxine and Brilliant Blue FCF, since adsorption reduced transversal dispersion of the sulfadimethoxine and dye. In non-stained area, residual concentrations of sulfadimethoxine were relatively lower than in stained areas. Therefore, Brilliant Blue FCF distribution can be used to approximate sulfadimethoxine movement in soil. However, presence of preferential flow networks found in undisturbed soil cores can enhance mobility of sulfadimethoxine and the tracers, due to faster flow velocities and non-equilibrium adsorption. Our findings showed that other dye tracers may also be applicable to identify transport pathways of various organic contaminants, of which physico-chemical properties are similar to those of the dye tracers. Preferential flow should be considered for drinking water managements and transport modelling, since this allows faster pollutants transport from their sources, and create critical consequences for groundwater quality and solute transport modelling.

A risk index for characterising flow pattern in soils using dye tracer distributions.

A novel risk index for the vulnerability of groundwater by pollutants is defined as the form parameter of the Pareto distribution and estimated from dye tracer experiments. The Pareto distribution appears as the limit distribution of the extreme value theory, which has been applied to an idealized model of drops that run along a path. The properties of the risk index are investigated by a Monte Carlo study, where the paths are modelled by means of Gaussian random fields. The method is applied to three profiles obtained from Brilliant Blue tracer experiments of the soil physics group at ETH Zurich. It is shown that a single profile can be rather well characterised by the risk index. However, due to the high variability of the dye tracer profiles, an estimated number of at least 15 profile pictures are necessary to characterise a soil.