Land cover composition determinants in the Uckermark (NE Germany) over a 220-year period

There is broad consensus that land use/cover has changed in central Europe over millennia. However, few studies have addressed the roles of the anthropogenic (socio-economic) and natural (biophysical) factors driving these changes over shorter periods (e.g., 100 years). In this study, we analyse the determinants of land cover composition at three discrete time periods (c. 1780, 1890, and 2000). We hypothesise that different anthropogenic and natural factors are the determinants of the main land cover types (arable fields, grasslands, and forests) and that the effects of natural and anthropogenic factors on the main land cover types differ among landscapes with highly dynamic and more stable forest-open land distributions. The study was carried out in the Uckermark region located in northeastern Germany. We compiled data on natural and anthropogenic factors (e.g. forest cover and number of inhabitants) of 65 municipalities in four landscape sections of equal size (10 × 10 km). Landscape sections were selected to reflect different dynamics (high/low) in conversion from forest to arable fields or grasslands and vice versa from 1780 to 2000. Averaged linear mixed-effect models explained between 7.5 and 81.2 % of the variance. The unique effect of anthropogenic factors varied from 2.1 to 18.7 % and that of natural factors varied from 0.2 to 43.4 %. In four of six models that included both types of factors, the natural factors were more influential than the anthropogenic factors. Except in three cases, anthropogenic and natural factors showed opposite effects on land cover types in more dynamic and more stable windows. Though the Uckermark region has been influenced by human activity for thousands of years, natural factors were a major determinant of land cover composition during all time periods, whereas anthropogenic factors became more important only during the latest time period under investigation.     

Porcine Blood and Liver as Sporadic Sources of Hepatitis E Virus (HEV) in the Production Chain of Offal-Derived Foodstuffs in Poland

Food and Environmental Virology - Pig’s blood and liver are valuable edible slaughter by-products which are also the major ingredients of offal-derived foodstuffs. The aim of the study was an...     

Chemical characteristics of trace metals in PM10 and their concentrated weighted trajectory analysis at Central Delhi, India

Trace metals associated with PM₁₀ aerosols and their variation during day and nighttime as well as during different seasons have been studied for the year 2012. PCA analysis suggested 5 PCs, which accounted for 86.8% cumulative variance. PC1 accounted for 30% with a significant loading of metals of anthropogenic origin, while PC2 showed 28% variance with the loading of metals of crustal origin. These trace metals showed seasonal distinct day and night time characteristics. The concentrations of Cu, Pb, and Cd were found to be higher during nighttime in all the seasons. Only Fe was observed with significantly higher mean concentrations during daytime of all seasons except monsoon. The highest mean values of Cu, Cd, Zn, and Pb during post-monsoon might be attributed to winds advection over the regions of waste/biomass burning and industrial activities in Punjab and Haryana regions. Furthermore, concentration weighted trajectory analysis suggested that metals of crustal origin were contributed by long-range transport while metals of anthropogenic and industrial activities were contributed by regional/local source regions.     

Photosensitized Oxidation of Cyanide in Aqueous Solutions of Photoactive Modified Hydroxyethylcellulose

Novel water-soluble polymeric photosensitizers based on a natural polymer, naphthalene-modified hydroxyethylcellulose (HENC), were obtained and used for the photooxidation of cyanide. The reaction leads to the formation of cyanate. The process occurs via photoinduced electron transfer from CN⁻ to the naphthalene or naphthoquinone polymeric chromophores. The kinetics of the reaction depend on the degree of substitution of HENC, its concentration, and pH of the solution. The polymers can be easily removed after reaction as prolonged irradiation leads to their photodegradation.     

Water quality in rice-growing watersheds in a Mediterranean climate

Rice (Oryza sativa L.) agriculture is estimated to cover 161 million ha of land on Earth, with 10% grown in temperate regions. Currently there are strong concerns about surface water nutrient pollution, and the purpose of this study was to determine the impacts of temperate rice cultivation on nutrient dynamics at the small watershed scale. Over the course of the 2008 growing season (May through September), bi-weekly grab samples were collected from outlets of 11 agricultural subwatersheds in California. Samples were analyzed for NO₃-N, NH₄-N, PO₄-P, K, and dissolved organic nitrogen (DON) concentrations, and the average values across all subwatersheds and sampling dates were 0.22, 0.031, 0.047, 1.36, and 0.32 mg L⁻¹, respectively. Linear mixed effects analysis was used to evaluate the magnitude of relationships between nutrient concentration and flux and subwatershed characteristics (i.e. percent soil clay and organic matter, percent rice area, irrigation water reuse, subwatershed discharge, irrigated area, and time, measured as the day in the growing season). For all nutrients, flux decreased over time and increased with discharge. Concentrations of K and DON were highest at the start and end of the growing season. Concentrations of NH₄-N were near non-detect levels, with the exception of a peak in mid-July, which corresponds to when many growers top-dress rice fields with N fertilizer. Nitrate-N concentration and flux decreased with percent rice area, whereas PO₄-P concentrations increased with percent rice area, indicating that rice area should be considered in future watershed-scale studies of nutrient discharge. In all subwatersheds, the discharge loads of K were smaller than surface water input loads, while NO₃-N, NH₄-N, PO₄-P, and DON discharge loads exceeded input loads when total growing season discharge was greater than 3500-6600 m³ ha⁻¹. This implies that the management of subwatershed discharge can be used to control nutrient export from rice-growing areas.     

The response of temperate aquatic ecosystems to global warming: novel insights from a multidisciplinary project

This article serves as an introduction to this special issue of Marine Biology, but also as a review of the key findings of the AQUASHIFT research program which is the source of the articles published in this issue. AQUASHIFT is an interdisciplinary research program targeted to analyze the response of temperate zone aquatic ecosystems (both marine and freshwater) to global warming. The main conclusions of AQUASHIFT relate to (a) shifts in geographic distribution, (b) shifts in seasonality, (c) temporal mismatch in food chains, (d) biomass responses to warming, (e) responses of body size, (f) harmful bloom intensity, (f), changes of biodiversity, and (g) the dependence of shifts to temperature changes during critical seasonal windows.     

Culturomics and metagenomics: In understanding of environmental resistome

State of the art of culturomics and metagenomics to study resistome was presented. The combination of culturomics and metagenomics approaches was proposed. The research directions of antibiotic resistance study has been suggested. Pharmaceutical residues, mainly antibiotics, have been called “emerging contaminants” in the environment because of their increasing frequency of detection in aquatic and terrestrial systems and their sublethal ecological effects. Most of them are undiscovered. Both human and veterinary pharmaceuticals, including antibiotics, are introduced into the environment via many different routes, including discharges from municipal wastewater treatment plants and land application of animal manure and biosolids to fertilize croplands. To gain a comprehensive understanding of the widespread problem of antibiotic resistance, modern and scientific approaches have been developed to gain knowledge of the entire antibiotic-resistant microbiota of various ecosystems, which is called the resistome. In this review, two omics methods, i.e. culturomics, a new approach, and metagenomics, used to study antibiotic resistance in environmental samples, are described. Moreover, we discuss how both omics methods have become core scientific tools to characterize microbiomes or resistomes, study natural communities and discover new microbes and new antibiotic resistance genes from environments. The combination of the method for get better outcome of both culturomics and metagenomics will significantly advance our understanding of the role of microbes and their specific properties in the environment.     

Identifying the possibilities and pitfalls of conducting IUCN Red List assessments from remotely sensed habitat information based on insights from poorly known Cuban mammals

The International Union for Conservation of Nature's Red List of Threatened Species (RLS) is the key global tool for objective, repeatable assessment of species’ extinction risk status, and plays an essential role in tracking biodiversity loss and guiding conservation action. Satellite remote sensing (SRS) data sets on global ecosystem distributions and functioning show exciting potential for informing range-based RLS assessment, but their incorporation has been restricted by low temporal resolution and coverage of data sets, lack of incorporation of degradation-driven habitat loss, and noninclusion of assumptions related to identification of changing habitat distributions for taxa with varying habitat dependency and ecologies. For poorly known mangrove-associated Cuban hutias (Mesocapromys spp.), we tested the impact of possible assumptions regarding these issues on range-based RLS assessment outcomes. Specifically, we used annual (1985–2018) Landsat data and land-cover classification and habitat degradation analyses across different internal time series slices to simulate range-based RLS assessments for our case study taxa to explore potential assessment uncertainty arising from temporal SRS data set coverage, incorporating proxies of (change in) habitat quality, and assumptions on spatial scaling of habitat extent for RLS parameter generation. We found extensive variation in simulated species-specific range-based RLS assessments, and this variation was mostly associated with the time series over which parameters were estimated. However, results of some species-specific assessments differed by up to 3 categories (near threatened to critically endangered) within the same time series, due to the effects of incorporating habitat quality and the spatial scaling used in RLS parameter estimation. Our results showed that a one-size-fits-all approach to incorporating SRS information in RLS assessment is inappropriate, and we urge caution in conducting range-based assessments with SRS for species for which habitat dependence on specific ecosystem types is incompletely understood. We propose novel revisions to parameter spatial scaling guidelines to improve integration of existing time series data on ecosystem change into the RLS assessment process.     

The CPCAT as a novel tool to overcome the shortcomings of NOEC/LOEC statistics in ecotoxicology: a simulation study to evaluate the statistical power

Species reproduction is an important determinant of population dynamics. As such, this is an important parameter in environmental risk assessment. The closure principle computational approach test (CPCAT) was recently proposed as a method to derive a NOEC/LOEC for reproduction count data such as the number of juvenile Daphnia. The Poisson distribution used by CPCAT can be too restrictive as a model of the data-generating process. In practice, the generalized Poisson distribution could be more appropriate, as it allows for inequality of the population mean \(\mu\) and the population variance \(\sigma ^2\). It is of fundamental interest to explore the statistical power of CPCAT and the probability of determining a regulatory relevant effect correctly. Using a simulation, we varied between Poisson distribution (\(\mu =\sigma ^2\)) and generalized Poisson distribution allowing for over-dispersion (\(\mu <\sigma ^2\)) and under-dispersion (\(\mu >\sigma ^2\)). The results indicated that the probability of detecting the LOEC/NOEC correctly was \(\ge 0.8\) provided the effect was at least 20% above or below the mean level of the control group and mean reproduction of the control was at least 50 individuals while over-dispersion was missing. Specifically, under-dispersion increased, whereas over-dispersion reduced the statistical power of the CPCAT. Using the well-known Hampel identifier, we propose a simple and straight forward method to assess whether the data-generating process of real data could be over- or under-dispersed.