History matters: Heterotrophic microbial community structure and function adapt to multiple stressors

Ecosystem functions in streams (e.g., microbially mediated leaf litter breakdown) are threatened globally by the predicted agricultural intensification and its expansion into pristine areas, which is associated with increasing use of fertilizers and pesticides. However, the ecological consequences may depend on the disturbance history of microbial communities. To test this, we assessed the effects of fungicides and nutrients (four levels each) on the structural and functional resilience of leaf‐associated microbial communities with differing disturbance histories (pristine vs. previously disturbed) in a 2 × 4 × 4‐factorial design (n = 6) over 21 days. Microbial leaf breakdown was assessed as a functional variable, whereas structural changes were characterized by the fungal community composition, species richness, biomass, and other factors. Leaf breakdown by the pristine microbial community was reduced by up to 30% upon fungicide exposure compared with controls, whereas the previously disturbed microbial community increased leaf breakdown by up to 85%. This significant difference in the functional response increased in magnitude with increasing nutrient concentrations. A pollution‐induced community tolerance in the previously disturbed microbial community, which was dominated by a few species with high breakdown efficacies, may explain the maintained function under stress. Hence, the global pressure on pristine ecosystems by agricultural expansion is expected to cause a modification in the structure and function of heterotrophic microbial communities, with microbially mediated leaf litter breakdown likely becoming more stable over time as a consequence of fungal community adaptions.     

Genetic analysis reveals candidate species in the Scinax catharinae clade (Amphibia: Anura) from Central Brazil

Scinax (Anura: Hylidae) is a species-rich genus of amphibians (113 spp.), divided into five species groups by morphological features. Cladistic analyses however revealed only two monophyletic clades in these groups: Scinax catharinae and Scinax ruber. Most species from the S. catharinae clade are found in Atlantic rainforest, except for Scinax canastrensis,S. centralis, S. luizotavioi, S. machadoi,S. pombali and S. skaios. In the present work, specimens of Scinax collected in Chapada dos Guimarães, central Brazil, were morphologically compatible with species from theS. catharinae group. On the other hand, genetic analysis based on mitochondrial (16S and 12S) and nuclear (rhodopsin) sequences revealed a nucleotide divergence of 6 to 20% between Scinax sp. and other congeners from the Brazilian savannah (Cerrado). Accordingly, Bayesian inference placed Scinax sp. in the S. catharinae clade with high support values. Hence, these findings strongly indicate the presence of a new species in the S. catharinae clade from the southwestern portion of the Brazilian savannah. To be properly validated as a novel species, detailed comparative morphological and bioacustic studies with other taxa from Brazil such asS. canastrensis, S. centralis, S. luizotavioi, S. machadoi, S. pombali and S. skaios are required.     

Aging of TiO2 Nanoparticles Transiently Increases Their Toxicity to the Pelagic Microcrustacean Daphnia magna

During their aquatic life cycle, nanoparticles are subject to environmentally driven surface modifications (e.g. agglomeration or coating) associated with aging. Although the ecotoxicological potential of nanoparticles might be affected by these processes, only limited information about the potential impact of aging is available. In this context, the present study investigated acute (96 h) and chronic (21 d) implications of systematically aged titanium dioxide nanoparticles (nTiO₂; ~90 nm) on the standard test species Daphnia magna by following the respective test guidelines. The nTiO₂ were aged for 0, 1, 3 and 6 d in media with varying ionic strengths (Milli-Q water: approx. 0.00 mmol/L and ASTM: 9.25 mmol/L) in the presence or absence of natural organic matter (NOM). Irrespective of the other parameters, aging in Milli-Q did not change the acute toxicity relative to an unaged control. In contrast, 6 d aged nTiO₂ in ASTM without NOM caused a fourfold decreased acute toxicity. Relative to the 0 d aged particles, nTiO₂ aged for 1 and 3 d in ASTM with NOM, which is the most environmentally-relevant setup used here, significantly increased acute toxicity (by approximately 30%), while a toxicity reduction (60%) was observed for 6 d aged nTiO₂. Comparable patterns were observed during the chronic experiments. A likely explanation for this phenomenon is that the aging of nTiO₂ increases the particle size at the start of the experiment or the time of the water exchange from <100 nm to approximately 500 nm, which is the optimal size range to be taken up by filter feeding D. magna. If subjected to further agglomeration, larger nTiO₂ particles, however, cannot be retained by the daphnids’ filter apparatus ultimately reducing their ecotoxicological potential. This non-linear pattern of increasing and decreasing nTiO₂ related toxicity over the aging duration, highlights the knowledge gap regarding the underlying mechanisms and processes. This understanding seems, however, fundamental to predict the risks of nanoparticles in the field.     

Complex adjustments of photosynthetic potentials and internal diffusion conductance to current and previous light availabilities and leaf age in Mediterranean evergreen species Quercus ilex

Mature non-senescent leaves of evergreen species become gradually shaded as new foliage develops and canopy expands, but the interactive effects of integrated light during leaf formation (Q(int)G), current light (Q(int)C) and leaf age on foliage photosynthetic competence are poorly understood. In Quercus ilex L., we measured the responses of leaf structural and physiological variables to Q(int)C and Q(int)G for four leaf age classes. Leaf aging resulted in increases in leaf dry mass per unit area (M(A)), and leaf dry to fresh mass ratio (D(F)) and decreases in N content per dry mass (N(M)). N content per area (N(A)) was independent of age, indicating that decreases in N(M) reflected dilution of leaf N because of accumulation of dry mass (NA = N(M) M(A)). M(A), D(F) and N(A) scaled positively with irradiance, whereas these age-specific correlations were stronger with leaf growth light than with current leaf light. Area-based maximum ribulose 1,5-bisphosphate carboxylase/oxygenase (Rubisco) carboxylase activity (V(cmax)A), capacity for photosynthetic electron transport (J(max)A) and the rate of non-photorespiratory respiration in light (R(d)A) were also positively associated with irradiance. Differently from leaf structural characteristics, for all data pooled, these relationships were stronger with current light with little differences among leaves of different age. Acclimation to current leaf light environment was achieved by light-dependent partitioning of N in rate-limiting proteins. Mass-based physiological activities decreased with increasing leaf age, reflecting dilution of leaf N and a larger fraction of non-photosynthetic N in older leaves. This resulted in age-dependent modification of leaf photosynthetic potentials versus N relationships. Internal diffusion conductance (g(m)) per unit area (g(m)A) increased curvilinearly with increasing irradiance for two youngest leaf age classes and was independent of light for older leaves. In contrast, g(m) per dry mass (g(m)M) was negatively associated with light in current-year leaves. Greater photosynthetic potentials and moderate changes in diffusion conductance resulted in greater internal diffusion limitations of photosynthesis in higher light. Both area- and mass-based g(m) decreased with increasing leaf age. The decrease in diffusion conductance was larger than changes in photosynthetic potentials, leading to larger CO2 drawdown from leaf internal air space to chloroplasts (delta(c)) in older leaves. The increases in diffusion limitations in older leaves and at higher light scaled with age- and light-dependent increases in MA and D(F). Overall, our study demonstrates a large potential of foliage photosynthetic acclimation to changes in leaf light environment, but also highlights enhanced structural diffusion limitations in older leaves that result from leaf structural acclimation to previous rather than to current light environment and accumulation of structural compounds with leaf age.     

A fuzzy anomaly indicator for environmental monitoring at continental scale

Environmental status assessment and monitoring can be performed by the integration of multi-source datasets at continental and global scales. We propose a methodology for the development of a new anomaly indicator (AI) which can highlight the occurrence of anomalous conditions in a synthetic fashion by analysis of a set of spatial input data. Anomalous conditions are defined relative to long-term average assumed as normal or reference status of the vegetated land surface. The indicator is defined according to fuzzy set theory which is a powerful means of handling uncertain and imprecise knowledge of environmental systems. The indicator integrates, in an innovative way, the anomaly scores of a set of contributing factors extracted from the analysis of historical time series, mainly of Earth observations data. These time series are used to automatically derive the fuzzy membership functions that quantify the contribution of each factor to the final indicator. No reference data and expert knowledge are strictly required for the implementation of the AI although the methodology allows customization where this type of information is available. The method was tested over the African continent for the period 1996–2002; monthly AI values were derived with input datasets of vegetation phenology and rainfall estimates. The output AI continental maps bring new information by integrating multiple factors and they highlight patterns of anomalous conditions of the status of the environment. The analysis of the correlation with the El Niño Southern Oscillation (ENSO) shows that the AI is able to identify the effects of this phenomenon and its spatio-temporal dynamics. The 1997–1998 and 2000–2001 ENSO events are clearly highlighted by the highest AI values in specific regions of the continent. The indicator proposed is a valuable tool which can help guide in depth and detailed investigations of environmental conditions at local scale.     

Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits

The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties (EFPs). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity (GPP) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFPs and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site‐years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R² = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of eddy covariance fluxes and plant traits in time and space is shown to be highly relevant to better understand the importance of intra‐ and interspecific trait variation on ecosystem functioning.     

BayMeth: improved DNA methylation quantification for affinity capture sequencing data using a flexible Bayesian approach

Affinity capture of DNA methylation combined with high-throughput sequencing strikes a good balance between the high cost of whole genome bisulfite sequencing and the low coverage of methylation arrays. We present BayMeth, an empirical Bayes approach that uses a fully methylated control sample to transform observed read counts into regional methylation levels. In our model, inefficient capture can readily be distinguished from low methylation levels. BayMeth improves on existing methods, allows explicit modeling of copy number variation, and offers computationally efficient analytical mean and variance estimators. BayMeth is available in the Repitools Bioconductor package.