Use of autonomous audio recordings for the rapid inventory of birds in the white‐sand forests of the Peruvian Amazon

White‐sand forests are patchily distributed ecosystems covering just 5% of Amazonia that host many specialist species of birds not found elsewhere, and these forests are threatened due to their small size and human exploitation of sand for construction projects. As a result, many species of birds that are white‐sand specialists are at risk of extinction, and immediate conservation action is paramount for their survival. Our objective was to evaluate current survey methods and determine the relative effect of the size of patches of these forests on the presence or absence of white‐sand specialists. Using point counts and autonomous recorders, we surveyed avian assemblages occupying patches of white‐sand forest in the Peruvian Amazon in April 2018. Overall, we detected 126 species, including 21 white‐sand forest specialists. We detected significantly more species of birds per survey point with autonomous recorders than point counts. We also found a negative relationship between avian species richness and distance from the edge of patches of white‐sand forest, but a significant, positive relationship when only counting white‐sand specialists. Although we detected more species with autonomous recorders, point counts were more effective for detecting canopy‐dwelling passerines. Therefore, we recommend that investigators conducting surveys for rare and patchily distributed species in the tropics use a mixed‐method approach that incorporates both autonomous recorders and visual observation. Finally, our results suggest that conserving large, continuous patches of white‐sand forest may increase the likelihood of survival of species of birds that are white‐sand specialists.     

Mechano- and pH-sensing convergence on Ca2+-mobilising proteins – A recipe for cancer?

Alterations in the (bio)chemical and physical microenvironment of cells accompany and often promote disease formation and progression. This is particularly well established for solid cancers, which are typically stiffer than the healthy tissue in which they arise, and often display profound acidification of their interstitial fluid. Cell surface receptors can sense changes in the mechanical and (bio)chemical properties of the surrounding extracellular matrix and fluid, and signalling through these receptors is thought to play a key role in disease development and advancement. This review will look at ion channels and G protein coupled receptors that are activated by mechanical cues and extracellular acidosis, and stimulation of which results in increases in intracellular Ca²⁺ concentrations. Cellular Ca²⁺ levels are dysregulated in cancer as well as cancer-associated cells, and mechano- and proton-sensing proteins likely contribute to these aberrant intracellular Ca²⁺ signals, making them attractive targets for therapeutic intervention.     

Zoning eco-environmental vulnerability for environmental management and protection

Eco-environmental vulnerability assessment is crucial for environmental and resource management. However, evaluation of eco-environmental vulnerability over large areas is a difficult and complex process because it is affected by many variables including hydro-meteorology, topography, land resources, and human activities. The Thua Thien – Hue Province and its largest river system, the Perfume River, are vital to the social-economic development of the north central coastal region of Vietnam, but there is no zoning system for environmental protection in this region. An assessment framework is proposed to evaluate the vulnerable eco-environment in association with 16 variables with 6 of them constructed from Landsat 8 satellite image products. The remaining variables were extracted from digital maps. Each variable was evaluated and spatially mapped with the aid of an analytical hierarchy process (AHP) and geographical information system (GIS). An eco-environmental vulnerability map is assorted into six vulnerability levels consisting of potential, slight, light, medium, heavy, and very heavy vulnerabilities, representing 14%, 27%, 17%, 26%, 13%, 3% of the study area, respectively. It is found that heavy and very heavy vulnerable areas appear mainly in the low and medium lands where social-economic activities have been developing rapidly. Tiny percentages of medium and heavy vulnerable levels occur in high land areas probably caused by agricultural practices in highlands, slash and burn cultivation and removal of natural forests with new plantation forests. Based on our results, three ecological zones requiring different development and protection solutions are proposed to restore local eco-environment toward sustainable development. The proposed integrated method of remote sensing (RS), GIS, and AHP to evaluate the eco-environmental vulnerability is useful for environmental protection and proper planning for land use and construction in the future.     

Macroecology in the age of Big Data – Where to go from here?

Recent years have seen an exponential increase in the amount of data available in all sciences and application domains. Macroecology is part of this “Big Data” trend, with a strong rise in the volume of data that we are using for our research. Here, we summarize the most recent developments in macroecology in the age of Big Data that were presented at the 2018 annual meeting of the Specialist Group Macroecology of the Ecological Society of Germany, Austria and Switzerland (GfÖ). Supported by computational advances, macroecology has been a rapidly developing field over recent years. Our meeting highlighted important avenues for further progress in terms of standardized data collection, data integration, method development and process integration. In particular, we focus on (a) important data gaps and new initiatives to close them, for example through space- and airborne sensors, (b) how various data sources and types can be integrated, (c) how uncertainty can be assessed in data-driven analyses and (d) how Big Data and machine learning approaches have opened new ways of investigating processes rather than simply describing patterns. We discuss how Big Data opens up new opportunities, but also poses new challenges to macroecological research. In the future, it will be essential to carefully assess data quality, the reproducibility of data compilation and analytical methods, and the communication of uncertainties. Major progress in the field will depend on the definition of data standards and workflows for macroecology, such that scientific quality and integrity are guaranteed, and collaboration in research projects is made easier.     

Shewanella biofilm development and engineering for environmental and bioenergy applications

The genus Shewanella comprises about 70 species of Gram-negative, facultative anaerobic bacteria inhabiting various environments, which have shown great potential in various biotechnological applications ranging from environmental bioremediation, metal(loid) recovery and material synthesis to bioenergy generation. Most environmental and energy applications of Shewanella involve the biofilm mode of growth on surfaces of solid minerals or electrodes. In this article, we first provide an overview of Shewanella biofilm biology with the focus on biofilm dynamics, biofilm matrix, and key signalling systems involved in Shewanella biofilm development. Then we review strategies recently exploited to engineer Shewanella biofilms to improve biofilm-mediated bioprocesses.     

Genome analysis of Pseudomonas aeruginosa by field inversion gel electrophoresis

Abstract The genome of Pseudomonas aeruginosa was analysed by digestion with rare-cutting restriction endonucleases and subsequent field inversion gel electrophoresis (FIGE). P. aeruginosa strain PAO and the 17 IATS strains were investigated. Each strain displayed a unique pattern of restriction fragments. Digestion with Dra I and Ssp I yielded, respectively 7–11 and 2–5 fragments of more than 130 kb in size, indicating the non-random occurrence of AT-rich sequences in the P. aeruginosa genome. The genome size of P. aeruginosa PAO was estimated to be (2.2 ± 0.3) × 10⁶ bp. The applications of DNA fingerprinting for gene cloning, construction of a physical chromosome map, and epidemiological studies, are discussed.