Five main phases of landscape degradation revealed by a dynamic mesoscale model analysing the splitting, shrinking, and disappearing of habitat patches

The ecological consequences of habitat loss and fragmentation have been intensively studied on a broad, landscape-wide scale, but have less been investigated on the finer scale of individual habitat patches, especially when considering dynamic turnovers in the habitability of sites. We study changes to individual patches from the perspective of the inhabitant organisms requiring a minimum area for survival. With patches given by contiguous assemblages of discrete habitat sites, the removal of a single site necessarily causes one of the following three elementary local events in the affected patch: splitting into two or more pieces, shrinkage without splitting, or complete disappearance. We investigate the probabilities of these events and the effective size of the habitat removed by them from the population's living area as the habitat landscape gradually transitions from pristine to totally destroyed. On this basis, we report the following findings. First, we distinguish four transitions delimiting five main phases of landscape degradation: (1) when there is only a little habitat loss, the most frequent event is the shrinkage of the spanning patch; (2) with more habitat loss, splitting becomes significant; (3) splitting peaks; (4) the remaining patches shrink; and (5) finally, they gradually disappear. Second, organisms that require large patches are especially sensitive to phase 3. This phase emerges at a value of habitat loss that is well above the percolation threshold. Third, the effective habitat loss caused by the removal of a single habitat site can be several times higher than the actual habitat loss. For organisms requiring only small patches, this amplification of losses is highest during phase 4 of the landscape degradation, whereas for organisms requiring large patches, it peaks during phase 3

Optimal L\'{e}vy-flight foraging in a finite landscape

We present a simple model to study L\'{e}vy-flight foraging in a finite landscape with countable targets. In our approach, foraging is a step-based exploratory random search process with a power-law step-size distribution $P(l) \propto l^{-\mu}$. We find that, when the termination is regulated by a finite number of steps $N$, the optimum value of $\mu$ that maximises the foraging efficiency can vary substantially in the interval $\mu \in (1,3)$, depending on the landscape features (landscape size and number of targets). We further demonstrate that subjective returning can be another significant factor that affects the foraging efficiency in such context. Our results suggest that L\'{e}vy-flight foraging may arise through an interaction between the environmental context and the termination of exploitation, and particularly that the number of steps can play an important role in this scenario which is overlooked by most previous work. Our study not only provides a new perspective on L\'{e}vy-flight foraging, but also opens new avenues for investigating the interaction between foraging dynamics and environment as well as offers a realistic framework for analysing animal movement patterns from empirical data.Comment: 25 pages, 6 figure

Melaminium nitrate–melamine–water (1/1/1). Corrigendum

Corrigendum to Acta Cryst. (2010), E66, o3033–o3034

Foregrounding the Code: Computational Chemistry Instructional Activities Using a Highly Readable Fluid Simulation Code

Computational chemistry instructional activities are often based around students running chemical simulations via a graphical user interface (GUI). GUI-based activities offer many advantages, as they enable students to run chemical simulations with a few mouse clicks. Although these activities are excellent for introducing students to the capabilities of chemical simulations, the disadvantage is that the students’ experience is not representative of how professional computational chemists work. Just as it is important that students in an organic chemistry instructional lab gain hands-on experience with equipment commonly used by professional organic chemists, students of computational chemistry must gain hands-on experience with coding, as professional computational chemists do not rely on GUIs; we write code. Motivated by the need for instructional activities that provide hands-on experience with computer code, a pair of activities were created around a free lightweight (runs on standard laptops) open-source Lennard-Jones (LJ) fluid simulation code written in Python, a programming language that prioritizes readability. The first activity, aimed at undergraduate physical chemistry lab courses, involves students writing Python code in a Jupyter Notebook that is used to run LJ simulations and fit a van der Waals gas model to data produced by the LJ fluid simulations. The second is a jigsaw activity, aimed at advanced undergraduate or graduate students, where students are assigned different sections of the LJ fluid simulation code, and must demonstrate the functionality of their section to the class by both giving an oral presentation and sharing a Jupyter Notebook demonstration of their own design

Development of localized surface plasmon resonance biosensors for the detection of Brettanomyces bruxellensis in wine

Incident light interacting with noble-metal nanoparticles with smaller sizes than the wavelength of the incident light induces localized surface plasmon resonance (LSPR). In this work a gold nanostructured surface was used for the immobilization of a 5\u2032 end Thiol modified DNA probe to develop a LSPR nanobiosensor for the detection of the spoiler wine yeast Brettanomyces bruxellensis. Gold was evaporated to obtain a gold thickness of 4 nm. DNA (2 \u3bcL) from the target microorganism and the negative control at various concentrations were used to test the specificity and sensitivity of the LSPR technique. Changes in the optical properties of the nanoparticles due to DNA-probe binding are reflected in the shift of LSPR extinction maximum (\u3bbmax). The results obtained using as target microorganism B. bruxellensis, and as negative control Saccharomyces cerevisiae demonstrated the specificity of both the DNA-probe and the protocol. The LSPR spectrophotometry technique detects 0.1 ng/\u3bcL DNA target confirming the possibility to utilize this system for the detection of pathogen microorganisms present in low amount in food and beverage samples. \ua9 2015 Elsevier B.V. All rights reserved

Melaminium nitrate–melamine–water (1/1/1)

In the crystal structure of the title salt, C3H7N6 +·NO3 −·C3H6N6·H2O, the asymmetric unit consists of two neutral melamine (1,3,5-triazine-2,4,6-triamine) mol­ecules, two melaminium cations, two nitrate anions and two solvent water mol­ecules. One of the nitrate anions is disordered over two sets of positions, with a refined occupancy ratio of 0.909 (3):0.091 (3). The cations and neutral mol­ecules are approximately planar, with maximum deviations of 0.018 (2), 0.024 (2), 0.019 (2) and 0.007 (2) Å for each, respectively. In the crystal structure, melaminium cations and netural melamine mol­ecules self-assemble via N—H⋯N hydrogen bonds to form a supra­molecular hexa­gonal-shaped motif. In addition, the nitrate anions and water mol­ecules are connected by N—H⋯O hydrogen bonds to form a three-dimensional network

Plant-microbial interactions facilitate grassland species coexistence at the community level

Interspecific competition and plant-soil feedbacks are powerful drivers of plant community structure. However, across a range of edaphic conditions the interactive effects of these drivers on complex plant communities remain unclear. For example, plant-soil feedback studies focus on soil trained by a single plant species. We developed a method to assess effects of plant-microbial interactions (PMI) on a complex plant community. We established mesocosms with 13 grassland species, grown individually or together, in overgrazed or restored soil, with or without soil microbial inoculum collected from a productive and diverse native grassland. We assessed biomass production as influenced by edaphic conditions, interspecific competition and PMI. Furthermore, we assessed potential influences of interspecific competition and edaphic conditions on strength and direction of PMI. Our results indicate PMI drives negative growth responses for graminoids while forbs experience positive growth responses. Generally, interspecific competition did not alter the magnitude or direction of PMI-mediated growth responses. Edaphic conditions altered the influence of soil microbial communities on individual plant growth while PMI facilitated plant evenness. In plant community mesocosms, PMI-associated benefits were observed in overgrazed soil. However, interspecific competition overwhelmed plant growth benefits associated with soil microbial communities when plant communities were grown in restored soil. In mesocosms containing dominant grass species, interspecific competition had negative effects on species coexistence, but both positive and negative PMI partially counterbalanced this influence on plant species evenness. Understanding these mechanisms may improve our capacity to manage diverse and productive grasslands by enabling prediction of plant community composition following disturbance and subsequent restoration

Gli1 enhances migration and invasion via up-regulation of MMP-11 and promotes metastasis in ERα negative breast cancer cell lines

Gli1 is an established oncogene and its expression in Estrogen Receptor (ER) α negative and triple negative breast cancers is predictive of a poor prognosis; however, the biological functions regulated by Gli1 in breast cancer have not been extensively evaluated. Herein, Gli1 was over-expressed or down-regulated (by RNA interference and by expression of the repressor form of Gli3) in the ERα negative, human breast cancer cell lines MDA-MB-231 and SUM1315. Reduced expression of Gli1 in these two cell lines resulted in a decrease in migration and invasion. Gli1 over-expression increased the migration and invasion of MDA-MB-231 cells with a corresponding increase in expression of MMP-11. Silencing MMP-11 in MDA-MB-231 cells that over-expressed Gli1 abrogated the Gli1-induced enhancement of migration and invasion. Sustained suppression of Gli1 expression decreased growth of MDA-MB-231 in vitro by increasing apoptosis and decreasing proliferation. In addition, silencing of Gli1 reduced the numbers and sizes of pulmonary metastases of MDA-MB-231 in an in vivo experimental metastasis assay. In summary, Gli1 promotes the growth, survival, migration, invasion and metastasis of ERα negative breast cancer. Additionally, MMP-11 is up-regulated by Gli1 and mediates the migration and invasion induced by Gli1 in MDA-MB-231