Arthropod and Pathogen Damage on Fossil and Modern Plants: Exploring the Origins and Evolution of Herbivory on Land.

The use of the functional feeding group-damage type system for analyzing arthropod and pathogen interactions with plants has transformed our understanding of herbivory in fossil plant assemblages by providing data, analyses, and interpretation of the local, regional, and global patterns of a 420-Myr history. The early fossil record can be used to answer major questions about the oldest evidence for herbivory, the early emergence of herbivore associations on land plants, and later expansion on seed plants. The subsequent effects of the Permian-Triassic ecological crisis on herbivore diversity, the resulting formation of biologically diverse herbivore communities on gymnosperms, and major shifts in herbivory ensuing from initial angiosperm diversification are additional issues that need to be addressed. Studies ofherbivory resulting from more recent transient spikes and longer-term climate trends provide important data that are applied to current global change and include herbivore community responses to latitude, altitude, and habitat. Ongoing paleoecological themes remaining to be addressed include the antiquity of modern interactions, differential herbivory between ferns and angiosperms, and origins of modern tropical forests. The expansion of databases that include a multitude of specimens; improvements in sampling strategies; development of new analytical methods; and, importantly, the ability to address conceptually stimulating ecological and evolutionary questions have provided new impetus in this rapidly advancing field.

A data driven gully head susceptibility map of Africa at 30 m resolution.

Predicting gully erosion at the continental scale is challenging with current generation models. Moreover, datasets reflecting gully erosion processes are still rather scarce, especially in Africa. This study aims to bridge this gap by collecting an extensive dataset and developing a robust, empirical model that predicts gully head density at high resolution for the African continent. We developed a logistic probability model at 30 m resolution that predicts the likelihood of gully head occurrence using currently available GIS data sources. To calibrate and validate this model, we used a new database of 31,531 gully heads, mapped over 1216 sites across Africa. The exact location of all gully heads was manually mapped by trained experts using high-resolution imagery available from Google Earth. This allowed the extraction of detailed information at the gully head scale, such as the local soil surface slope. Variables included in our empirical model are topography, climate, vegetation, soil characteristics and tectonic context. They are consistent with our current process-based understanding of gully formation and evolution. The model shows that gully occurrences mainly depend on slope steepness, soil texture and vegetation cover and to a lesser extent on rainfall intensity and tectonic activity. The combination of these factors allows for robust and fairly reliable predictions of gully head occurrences, with Areas Under the Curve for validation around 0.8. Based on these results, we present the first gully head susceptibility map for Africa at a 30 m resolution.

Rising temperature modulates pH niches of fen species.

Rising temperatures may endanger fragile ecosystems because their character and key species show different habitat affinities under different climates. This assumption has only been tested in limited geographical scales. In fens, one of the most endangered ecosystems in Europe, broader pH niches have been reported from cold areas and are expected for colder past periods. We used the largest European-scale vegetation database from fens to test the hypothesis that pH interacts with macroclimate temperature in forming realized niches of fen moss and vascular plant species. We calibrated the data set (29,885 plots after heterogeneity-constrained resampling) with temperature, using two macroclimate variables, and with the adjusted pH, a variable combining pH and calcium richness. We modelled temperature, pH and water level niches for one hundred species best characterizing European fens using generalized additive models and tested the interaction between pH and temperature. Fifty-five fen species showed a statistically significant interaction between pH and temperature (adj p Ë‚ .01). Forty-six of them (84%) showed a positive interaction manifested by a shift or restriction of their niche to higher pH in warmer locations. Nine vascular plants and no moss showed the opposite interaction. Mosses showed significantly greater interaction. We conclude that climate significantly modulates edaphic niches of fen plants, especially bryophytes. This result explains previously reported regional changes in realized pH niches, a current habitat-dependent decline of endangered taxa, and distribution changes in the past. A warmer climate makes growing seasons longer and warmer, increases productivity, and may lower the water level. These effects prolong the duration and intensity of interspecific competition, support highly competitive Sphagnum mosses, and, as such, force niches of specialized fen species towards narrower high-pH ranges. Recent anthropogenic landscape changes pose a severe threat to many fen species and call for mitigation measures to lower competition pressure in their refugia.

Interacting elevational and latitudinal gradients determine bat diversity and distribution across the Neotropics.

New World bats are heavily affected by the biophysical setting shaped by elevation and latitude. This study seeks to understand the patterns of bat species diversity across elevational, latitudinal and vegetation height gradients throughout the Neotropics. Systematically gathered putative and empirical data on bat species distribution across the entire Neotropics were examined using descriptive statistics, spatial interpolation of bat taxonomic, functional and phylogenetic diversity, generalized linear models, generalized linear mixed models and phylogenetic generalized least squares. We uncoupled the effects of elevation, latitude and vegetation height to predict Neotropical bat diversity, showing that dietary level, home range and habitat breadth were the most important ecological traits determining coarse-scale bat distributions. Latitude was largely responsible for sorting the regional species pool, whereas elevation appears to apply an additional local filter to this regional pool wherever tropical mountains are present, thereby shaping the structure of montane assemblages. Bats provide multiple ecosystem services and our results can help pinpoint priority areas for bat research and conservation across all Neotropics, elucidate the thresholds of species distributions, and highlight bat diversity hotspots at multiple scales.

Assembleias de morcegos neotropicais são fortemente moldadas pelo ambiente biofísico que, por sua vez, é determinado pela elevação e latitude. Buscamos compreender neste estudo os padrões de diversidade de espécies de morcegos em gradientes de altitude, latitude e altura da vegetação ao longo de todo o domínio neotropical. Examinamos dados teóricos e empíricos sobre a distribuição de espécies de morcegos neotropicais, coletados sistematicamente, usando estatística descritiva, interpolação espacial de diversidade taxonômica, funcional e filogenética, modelos lineares generalizados, modelos lineares generalizados mistos e modelos generalizados filogenéticos. Desacoplamos os efeitos da altitude, latitude e altura da vegetação para predizer a diversidade de morcegos neotropicais, mostrando que nível trófico, tamanho da área de vida e especificidade de uso de habitats foram os traços ecológicos mais importantes que determinam as distribuições de morcegos em grande escala. A latitude foi amplamente responsável por determinar o conjunto regional de espécies, enquanto que a elevação parece aplicar um filtro local adicional no conjunto quando na presença de montanhas tropicais, moldando assim a estrutura das assembleias montanas de morcegos. Os morcegos atuam em vários serviços ecossistêmicos e nossos resultados podem ajudar a identificar áreas prioritárias para pesquisa e conservação de morcegos em toda a região neotropical, elucidar os limites de distribuição de espécies e destacar pontos críticos de diversidade de morcegos em múltiplas escalas.

From Hydrometeorology to River Water Quality: Can a Deep Learning Model Predict Dissolved Oxygen at the Continental Scale?

Dissolved oxygen (DO) reflects river metabolic pulses and is an essential water quality measure. Our capabilities of forecasting DO however remain elusive. Water quality data, specifically DO data here, often have large gaps and sparse areal and temporal coverage. Earth surface and hydrometeorology data, on the other hand, have become largely available. Here we ask: can a Long Short-Term Memory (LSTM) model learn about river DO dynamics from sparse DO and intensive (daily) hydrometeorology data? We used CAMELS-chem, a new data set with DO concentrations from 236 minimally disturbed watersheds across the U.S. The model generally learns the theory of DO solubility and captures its decreasing trend with increasing water temperature. It exhibits the potential of predicting DO in "chemically ungauged basins", defined as basins without any measurements of DO and broadly water quality in general. The model however misses some DO peaks and troughs when in-stream biogeochemical processes become important. Surprisingly, the model does not perform better where more data are available. Instead, it performs better in basins with low variations of streamflow and DO, high runoff-ratio (>0.45), and winter precipitation peaks. Results here suggest that more data collections at DO peaks and troughs and in sparsely monitored areas are essential to overcome the issue of data scarcity, an outstanding challenge in the water quality community.

Transport of N and P in U.S. streams and rivers differs with land use and between dissolved and particulate forms.

We used a recently published, open-access data set of U.S. streamwater nitrogen (N) and phosphorus (P) concentrations to test whether watershed land use differentially influences N and P concentrations, including the relative availability of dissolved and particulate nutrient fractions. We tested the hypothesis that N and P concentrations and molar ratios in streams and rivers of the United States reflect differing nutrient inputs from three dominant land-use types (agricultural, urban and forested). We also tested for differences between dissolved inorganic nutrients and suspended particulate nutrient fractions to infer sources and potential processing mechanisms across spatial and temporal scales. Observed total N and P concentrations often exceeded reported thresholds for structural changes to benthic algae (58, 57% of reported values, respectively), macroinvertebrates (39% for TN and TP), and fish (41, 37%, respectively). The majority of dissolved N and P concentrations exceeded threshold concentrations known to stimulate benthic algal growth (85, 87%, respectively), and organic matter breakdown rates (94, 58%, respectively). Concentrations of both N and P, and total and dissolved N:P ratios, were higher in streams and rivers with more agricultural and urban than forested land cover. The pattern of elevated nutrient concentrations with agricultural and urban land use was weaker for particulate fractions. The % N contained in particles decreased slightly with higher agriculture and urbanization, whereas % P in particles was unrelated to land use. Particulate N:P was relatively constant (interquartile range = 2-7) and independent of variation in DIN:DIP (interquartile range = 22-152). Dissolved, but not particulate, N:P ratios were temporally variable. Constant particulate N:P across steep DIN:DIP gradients in both space and time suggests that the stoichiometry of particulates across U.S. watersheds is most likely controlled either by external or by physicochemical instream factors, rather than by biological processing within streams. Our findings suggest that most U.S. streams and rivers have concentrations of N and P exceeding those considered protective of ecological integrity, retain dissolved N less efficiently than P, which is retained proportionally more in particles, and thus transport and export high N:P streamwater to downstream ecosystems on a continental scale.

The interacting roles of climate, soils, and plant production on soil microbial communities at a continental scale.

Soil microbial communities control critical ecosystem processes such as decomposition, nutrient cycling, and soil organic matter formation. Continental scale patterns in the composition and functioning of microbial communities are related to climatic, biotic, and edaphic factors such as temperature and precipitation, plant community composition, and soil carbon, nitrogen, and pH. Although these relationships have been well explored individually, the examination of the factors that may act directly on microbial communities vs. those that may act indirectly through other ecosystem properties has not been well developed. To further such understanding, we utilized structural equation modeling (SEM) to evaluate a set of hypotheses about the direct and indirect effects of climatic, biotic, and edaphic variables on microbial communities across the continental United States. The primary goals of this work were to test our current understanding of the interactions among climate, soils, and plants in affecting microbial community composition, and to examine whether variation in the composition of the microbial community affects potential rates of soil enzymatic activities. A model of interacting factors created through SEM shows several expected patterns. Distal factors such as climate had indirect effects on microbial communities by influencing plant productivity, soil mineralogy, and soil pH, but factors related to soil organic matter chemistry had the most direct influence on community composition. We observed that both plant productivity and soil mineral composition were important indirect influences on community composition at the continental scale, both interacting to affect organic matter content and microbial biomass and ultimately community composition. Although soil hydrolytic enzymes were related to the moisture regime and soil carbon, oxidative enzymes were also affected by community composition, reflected in the abundance of soil fungi. These results highlight that soil microbial communities can be modeled within the context of multiple interacting ecosystem properties acting both directly and indirectly on their composition and function, and this provides a rich and informative context with which to examine communities. This work also highlights that variation in climate, microbial biomass, and microbial community composition can affect maximum rates of soil enzyme activities, potentially influencing rates of decomposition and nutrient mineralization in soils.

Effects of productivity on biodiversity in forest ecosystems across the United States and China.

In the global campaign against biodiversity loss in forest ecosystems, land managers need to know the status of forest biodiversity, but practical guidelines for conserving biodiversity in forest management are lacking. A major obstacle is the incomplete understanding of the relationship between site primary productivity and plant diversity, due to insufficient ecosystem-wide data, especially for taxonomically and structurally diverse forest ecosystems. We investigated the effects of site productivity (the site's inherent capacity to grow timber) on tree species richness across 19 types of forest ecosystems in North America and China through 3 ground-sourced forest inventory data sets (U.S. Forest Inventory and Analysis, Cooperative Alaska Forest Inventory, and Chinese Forest Management Planning Inventory). All forest types conformed to a consistent and highly significant (P < 0.001) hump-shaped unimodal relationship, of which the generalized coefficients of determination averaged 20.5% over all the forest types. That is, tree species richness first increased as productivity increased at a progressively slower rate, and, after reaching a maximum, richness started to decline. Our consistent findings suggest that forests of high productivity would sustain few species because they consist mostly of flat homogeneous areas lacking an environmental gradient along which a diversity of species with different habitats can coexist. The consistency of the productivity-biodiversity relationship among the 3 data sets we examined makes it possible to quantify the expected tree species richness that a forest stand is capable of sustaining, and a comparison between the actual species richness and the sustainable values can be useful in prioritizing conservation efforts.

Big eucalypts grow more slowly in a warm climate: evidence of an interaction between tree size and temperature.

Large trees are critical components of forest ecosystems, but are declining in many forests worldwide. We predicted that growth of large trees is more vulnerable than that of small trees to high temperatures, because respiration and tissue maintenance costs increase with temperature more rapidly than does photosynthesis and these costs may be disproportionately greater in large trees. Using 5 00 000 measurements of eucalypt growth across temperate Australia, we found that high temperatures do appear to impose a larger growth penalty on large trees than on small ones. Average stem diameter growth rates at 21 °C compared with 11 °C mean annual temperature were 57% lower for large trees (58 cm stem diameter), but only 29% lower for small trees (18 cm diameter). While our results are consistent with an impaired carbon budget for large trees at warmer sites, we cannot discount causes such as hydraulic stress. We conclude that slower growth rates will impede recovery from extreme events, exacerbating the effects of higher temperatures, increased drought stress and more frequent fire on the tall eucalypt forests of southern Australia.

Homogenization of bacterial plastisphere community in soil: a continental-scale microcosm study.

Microplastics alter niches of soil microbiota by providing trillions of artificial microhabitats, termed the "plastisphere." Because of the ever-increasing accumulation of microplastics in ecosystems, it is urgent to understand the ecology of microbes associated with the plastisphere. Here, we present a continental-scale study of the bacterial plastisphere on polyethylene microplastics compared with adjacent soil communities across 99 sites collected from across China through microcosm experiments. In comparison with the soil bacterial communities, we found that plastispheres had a greater proportion of Actinomycetota and Bacillota, but lower proportions of Pseudomonadota, Acidobacteriota, Gemmatimonadota, and Bacteroidota. The spatial dispersion and the dissimilarity among plastisphere communities were less variable than those among the soil bacterial communities, suggesting highly homogenized bacterial communities on microplastics. The relative importance of homogeneous selection in plastispheres was greater than that in soil samples, possibly because of the more uniform properties of polyethylene microplastics compared with the surrounding soil. Importantly, we found that the degree to which plastisphere and soil bacterial communities differed was negatively correlated with the soil pH and carbon content and positively related to the mean annual temperature of sampling sites. Our work provides a more comprehensive continental-scale perspective on the microbial communities that form in the plastisphere and highlights the potential impacts of microplastics on the maintenance of microbial biodiversity and ecosystem functioning.

Deciphering patterns in whole fish nitrogen isotopes on a continental scale.

Nitrogen isotopes (δ15N) have been used as an indicator of anthropogenic nitrogen loading at local and regional scales. We examined δ15N in fish from estuaries across the continental United States. In the summer of 2015, the U.S. Environmental Protection Agency's National Coastal Condition Assessment (NCCA) collected fish in 136 coastal waterbodies throughout the United States. Whole fish were analyzed by NCCA for metals, organic contaminants, and lipids. For this study, we also analyzed these fish for isotopes of nitrogen (N). NCCA collected water quality, nutrients, chlorophyll a, and sediment chemistry at each site. We used these data, along with fish life history and watershed land use, to examine how whole fish δ15N was related to these environmental variables using random forest regression models at national and ecoregional scales. At the national scale, fish δ15N were negatively related to total N:total phosphorous (P) ratios (TN:TP) in surface water and reflected differences between the P-limited, δ15N depleted sites in the Floridian ecoregion to sites in other regions. δ15N was lower on the Atlantic relative to the Pacific coast. When considered by region, TN:TP was an important predictor of fish δ15N in 4 of 9 ecoregions, with higher δ15N observed with increasing N limitation (lower TN:TP) Fish life history was also an important predictor of fish δ15N at both the national and ecoregional scale. Whole fish δ15N was positively associated with bioaccumulative contaminants such as PCBs and mercury. Although land use was related to δ15N in fish, it was location specific. This study showed that N stable isotopes reflected ecological conditions at both regional and continental scales.

An assessment of South American sediment fluxes under climate changes.

Climate change can affect all levels of society and the planet. Recent studies have shown its effects on sediment fluxes in several locations worldwide, which can impact ecosystems and infrastructure such as reservoirs. In this study, we focused on simulating sediment fluxes using projections of future climate change for South America (SA), a continent with a high sediment transport rate to the oceans. Here, we used four climate change data yielded by the Eta Regional Climate Model: Eta-BESM, Eta-CanESM2, Eta-HadGEM2-ES, and Eta-MIROC5. In addition, it was evaluated the RCP4.5 greenhouse gas emissions scenario from CMIP5, which represents a moderate scenario. Climate change data between 1961 and 1995 (past) and 2021 and 2055 (future) were used to simulate and compare changes that may occur in water and sediment fluxes using the hydrological-hydrodynamic and sediment model MGB-SED AS. The Eta climate projections provided input data to MGB-SED AS model, such as precipitation, air surface temperature, incident solar radiation, relative humidity, wind speed, and atmospheric pressure. Our results showed sediment fluxes are expected to reduce (increase) in north-central (south-central) SA. While a sediment transport (QST) increase >30 % might occur, a 28 % decrease is expected to occur in the water discharge for the main SA basins. The most significant QST reductions were estimated for the Doce (-54 %), Tocantins (-49 %), and Xingu (-34 %) rivers, while the most significant increases were estimated for the Upper Paraná (409 %), Juruá (46 %), and Uruguay (40 %) rivers. We also observed that different climate change signals over large basins can impact the river water composition, which could lead to a new composition of the Amazon basin waters in the future, accompanied by a significant increase in sediment concentration.

Flyway-scale analysis reveals that the timing of migration in wading birds is becoming later.

Understanding the implications of climate change for migratory animals is paramount for establishing how best to conserve them. A large body of evidence suggests that birds are migrating earlier in response to rising temperatures, but many studies focus on single populations of model species.Migratory patterns at large spatial scales may differ from those occurring in single populations, for example because of individuals dispersing outside of study areas. Furthermore, understanding phenological trends across species is vital because we need a holistic understanding of how climate change affects wildlife, especially as rates of temperature change vary globally.The life cycles of migratory wading birds cover vast latitudinal gradients, making them particularly susceptible to climate change and, therefore, ideal model organisms for understanding its effects. Here, we implement a novel application of changepoint detection analysis to investigate changes in the timing of migration in waders at a flyway scale using a thirteen-year citizen science dataset (eBird) and determine the influence of changes in weather conditions on large-scale migratory patterns.In contrast to most previous research, our results suggest that migration is getting later in both spring and autumn. We show that rates of change were faster in spring than autumn in both the Afro-Palearctic and Nearctic flyways, but that weather conditions in autumn, not in spring, predicted temporal changes in the corresponding season. Birds migrated earlier in autumn when temperatures increased rapidly, and later with increasing headwinds.One possible explanation for our results is that migration is becoming later due to northward range shifts, which means that a higher proportion of birds travel greater distances and therefore take longer to reach their destinations. Our findings underline the importance of considering spatial scale when investigating changes in the phenology of migratory bird species.

Trophic level drives the host microbiome of soil invertebrates at a continental scale.

BACKGROUND: Increasing our knowledge of soil biodiversity is fundamental to forecast changes in ecosystem functions under global change scenarios. All multicellular organisms are now known to be holobionts, containing large assemblages of microbial species. Soil fauna is now known to have thousands of species living within them. However, we know very little about the identity and function of host microbiome in contrasting soil faunal groups, across different terrestrial biomes, or at a large spatial scale. Here, we examined the microbiomes of multiple functionally important soil fauna in contrasting terrestrial ecosystems across China. RESULTS: Different soil fauna had diverse and unique microbiomes, which were also distinct from those in surrounding soils. These unique microbiomes were maintained within taxa across diverse sampling sites and in contrasting terrestrial ecosystems. The microbiomes of nematodes, potworms, and earthworms were more difficult to predict using environmental data, compared to those of collembolans, oribatid mites, and predatory mites. Although stochastic processes were important, deterministic processes, such as host selection, also contributed to the assembly of unique microbiota in each taxon of soil fauna. Microbial biodiversity, unique microbial taxa, and microbial dark matter (defined as unidentified microbial taxa) all increased with trophic levels within the soil food web. CONCLUSIONS: Our findings demonstrate that soil animals are important as repositories of microbial biodiversity, and those at the top of the food web harbor more diverse and unique microbiomes. This hidden source of biodiversity is rarely considered in biodiversity and conservation debates and stresses the importance of preserving key soil invertebrates. Video abstract.

Rainfall erosivity in South America: Current patterns and future perspectives.

Rainfall erosivity is the driving factor for soil erosion and can be potentially affected by climate change, impacting agriculture and the environment. In this study, we sought to project the impact of climate change on the long-term average annual rainfall erosivity (R-factor) and mean annual precipitation in South America. The CanESM2, HadGEM2-ES, and MIROC5 global circulation models (GCMs) and the average of the GCMs (GCM-Ensemble) downscaled by the Eta/CPTEC model at a spatial resolution of 20 km in the representative concentration pathway (RCP) 8.5 were applied in this study. A geographical model to estimate the R-factor across South America was fitted. This model was based on latitude, longitude, altitude, and mean annual precipitation as inputs obtained from the WorldClim database. Using this model, the first R-factor map for South America was developed (for the baseline period: 1961-2005). The GCMs projected mean annual precipitation for three 30-year time periods (time slices: 2010-2040; 2041-2070; 2071-2099). These projections were used to run the R-factor model to assess the impact of climate change. It was observed that the changes were more pronounced in the Amazon Forest region (namely, the North Region, NR, and the Andes North Region, ANR) with a strong reduction in the mean annual precipitation and R-factor throughout the century. The highest increase in the R-factor was projected on the Central and South Andes regions (CAR and SAR) because of the increase in the mean annual precipitation projected by the GCMs. The GCMs pointed contradictory projections for the Central-South Region (CSR), indicating greater uncertainty. An increase in the R-factor was projected for this region, eastern Argentina, and southern Brazil, whereas a decrease in the R-factor was expected for southeastern Brazil. In general, the GCMs projected reductions in the R-factor and annual precipitation for South America, with the highest changes projected from the baseline to the 2010-2040 time slice.

Seasonal distribution, risks, and sources of endocrine disrupting chemicals in coastal waters: Will these emerging contaminants pose potential risks in marine environment at continental-scale?

Coastal waters are the critical ecologically fragile regions under the influence of the fastest economic developing pace and the extensive anthropogenic activities in coastal zone. Little information on the seasonal distribution, risks, and sources of endocrine disrupting chemicals (EDCs) which are emerging contaminants to pose potential risks at very low concentrations in coastal waters at continental-scale is available. This study investigated the coastline-based distribution, risks, and sources of target EDCs in coastal water of China. EDCs in coastal waters of China showed significant spatio-temporal variation with phenolic compounds serving as predominant EDCs. Bisphenol A (BPA) was detected in all water samples with average concentration of 449.2/186.3 ng/L in winter/summer while estrone was the main steroidal estrogen with the average concentration of 87.2/2.7 ng/L in winter/summer. EDCs in coastal waters of South China Sea Area showed higher concentrations. EDCs in coastal waters exerted high ecological risks and estrone/BPA averagely accounted for over 61%/71% of total risk quotient in winter/summer. Average estradiol equivalent concentration of all target EDCs reached 68.87/1.76 ng/L in winter/summer. EDCs in coastal waters did not pose potential non-cancer health risks for humans. The positive matrix factorization (PMF) model was firstly used to identify and quantify possible sources of EDCs. The PMF analysis showed that wastewater and sewage might be the main source for EDCs in coastal waters. EDCs in coastal waters showed high estradiol equivalent concentration and ecological risks at continental-scale, highlighting that EDCs contamination has become a crucial stress affecting the sustainable development of coastal regions.

Continental-scale spatio-temporal distribution of antibiotic resistance genes in coastal waters along coastline of China.

Antibiotic resistance genes (ARGs) have been frequently detected in various matrices all over the world to attract wide attention due to the potential risks. Rare information is available on the pollution of ARGs in the waters of critical ecologically fragile regions such as the coastal zone at a continental scale. Therefore, this study performed field sampling during winter and summer along 18000 km coastline of China to investigate the distribution of target ARGs in coastal waters at a continental scale. The absolute abundances of ARGs in coastal waters showed drastic spatio-temporal variation with a mean value of 8.79 × 104/1.39 × 105 copies/mL in summer/winter, much lower than those in tail water from the maricultural zone or wastewater. The average absolute abundance of class 1 integron-integrase gene (intI1) in coastal waters was 9.68 × 103/4.15 × 104 copies/mL in summer/winter, still lower than that in tail water or wastewater. Quinolone resistance genes were the dominant ARGs in coastal waters to account for over 50% of total ARGs in most of sampling sites. Bacterial communities in coastal waters showed significant difference both at phylum and genus levels. Abundances of ARGs in coastal waters of this study were comparable with those in other regions previously reported. Tail water and wastewater might be the essential sources of ARGs in coastal waters. The findings of this study provided comprehensive information on the pollution status of ARGs in coastal waters at a continental scale, indicating that ARGs pollution has become a crucial stress affecting the sustainable development of coastal regions.

Airborne Alternaria and Cladosporium fungal spores in Europe: Forecasting possibilities and relationships with meteorological parameters.

Airborne fungal spores are prevalent components of bioaerosols with a large impact on ecology, economy and health. Their major socioeconomic effects could be reduced by accurate and timely prediction of airborne spore concentrations. The main aim of this study was to create and evaluate models of Alternaria and Cladosporium spore concentrations based on data on a continental scale. Additional goals included assessment of the level of generalization of the models spatially and description of the main meteorological factors influencing fungal spore concentrations. Aerobiological monitoring was carried out at 18 sites in six countries across Europe over 3 to 21 years depending on site. Quantile random forest modelling was used to predict spore concentrations. Generalization of the Alternaria and Cladosporium models was tested using (i) one model for all the sites, (ii) models for groups of sites, and (iii) models for individual sites. The study revealed the possibility of reliable prediction of fungal spore levels using gridded meteorological data. The classification models also showed the capacity for providing larger scale predictions of fungal spore concentrations. Regression models were distinctly less accurate than classification models due to several factors, including measurement errors and distinct day-to-day changes of concentrations. Temperature and vapour pressure proved to be the most important variables in the regression and classification models of Alternaria and Cladosporium spore concentrations. Accurate and operational daily-scale predictive models of bioaerosol abundances contribute to the assessment and evaluation of relevant exposure and consequently more timely and efficient management of phytopathogenic and of human allergic diseases.

Establishing geochemical background variation and threshold values for 59 elements in Australian surface soil.

During the National Geochemical Survey of Australia over 1300 top (0-10cm depth) and bottom (~60-80cm depth) sediment samples (including ~10% field duplicates) were collected from the outlet of 1186 catchments covering 81% of the continent at an average sample density of 1 site/5200km2. The <2mm fraction of these samples was analysed for 59 elements by ICP-MS following an aqua regia digestion. Results are used here to establish the geochemical background variation of these elements, including potentially toxic elements (PTEs), in Australian surface soil. Different methods of obtaining geochemical threshold values, which differentiate between background and those samples with unusually high element concentrations and requiring attention, are presented and compared to Western Australia's 'ecological investigation levels' (EILs) established for 14 PTEs. For Mn and V these EILs are so low that an unrealistically large proportion (~24%) of the sampled sites would need investigation in Australia. For the 12 remaining elements (As, Ba, Cd, Co, Cr, Cu, Hg, Mo, Ni, Pb, Sn and Zn) few sample sites require investigation and as most of these are located far from human activity centres, they potentially suggest either minor local contamination or mineral exploration potential rather than pollution. No major diffuse source of contamination by PTEs affects Australian soil at the continental scale. Of the statistical methods used to establish geochemical threshold values, the most pertinent results come from identifying breaks in cumulative probability distributions, the Tukey inner fence and the 98th percentile. Geochemical threshold values for 59 elements, including emerging 'high-tech' critical elements such as lanthanides, Be, Ga or Ge, for which no EILs currently exist, are presented.