Methodology for optimizing quadrat size in sparse vegetation surveys: A desert case study from the Tarim Basin.

Random sampling is an important approach to field vegetation surveys. However, sampling surveys in desert areas are difficult because determining an appropriate quadrat size that represent the sparse and unevenly distributed vegetation is challenging. In this study, we present a methodology for quadrat size optimization based on low-altitude high-precision unmanned aerial vehicle (UAV) images. Using the Daliyaboyi Oasis as our study area, we simulated random sampling and analyzed the frequency distribution and variation in the fractional vegetation cover (FVC) index of the samples. Our results show that quadrats of 50 m × 50 m size are the most representative for sampling surveys in this location. The method exploits UAV technology to rapidly acquire vegetation information and overcomes the shortcomings of traditional methods that rely on labor-intensive fieldwork to collect species-area relationship (SAR) data. Our method presents two major advantages: (1) speed and efficiency stemming from the application of UAV, which also effectively overcomes the difficulties posed in vegetation surveys by the challenging desert climate and terrain; (2) the large sample size enabled by the use of a sampling simulation. Our methodology is thus highly suitable for selecting the optimal quadrat size and making accurate estimates, and can improve the efficiency and accuracy of field vegetation sampling surveys.

Inferring symmetric and asymmetric interactions between animals and groups from positional data.

Interactions between domestic and wild species has become a global problem of growing interest. Global Position Systems (GPS) allow collection of vast records of time series of animal spatial movement, but there is need for developing analytical methods to efficiently use this information to unravel species interactions. This study assesses different methods to infer interactions and their symmetry between individual animals, social groups or species. We used two data sets, (i) a simulated one of the movement of two grazing species under different interaction scenarios by-species and by-individual, and (ii) a real time series of GPS data on the movements of sheep and deer grazing a large moorland plot. Different time series transformations were applied to capture the behaviour of the data (convex hull area, kth nearest neighbour distance, distance to centre of mass, Voronoi tessellation area, distance to past position) to assess their efficiency in inferring the interactions using different techniques (cross correlation, Granger causality, network properties). The results indicate that the methods are more efficient assessing by-group interaction than by-individual interaction, and different transformations produce different outputs of the nature of the interaction. Both species maintained a consistent by-species grouping structure. The results do not provide clear evidence of inter-species interaction based on the traditional framework of niche partitioning in the guild of large herbivores. In view of the transformation-dependent results, it seems that in our experimental framework both species co-exist showing complex interactions. We provide guidelines for the use of the different transformations with respect to study aims and data quality. The study attempts to provide behavioural ecologists with tools to infer animal interactions and their symmetry based on positional data recorded by visual observation, conventional telemetry or GPS technology.

Variability in the Effectiveness of Two Ornithological Survey Methods between Tropical Forest Ecosystems.

Birds are a frequently chosen group for biodiversity monitoring as they are comparatively straightforward and inexpensive to sample and often perform well as ecological indicators. Two commonly used techniques for monitoring tropical forest bird communities are point counts and mist nets. General strengths and weaknesses of these techniques have been well-defined; however little research has examined how their effectiveness is mediated by the ecology of bird communities and their habitats. We examine how the overall performance of these methodologies differs between two widely separated tropical forests-Cusuco National Park (CNP), a Honduran cloud forest, and the lowland forests of Buton Forest Reserves (BFR) located on Buton Island, Indonesia. Consistent survey protocols were employed at both sites, with 77 point count stations and 22 mist netting stations being surveyed in each location. We found the effectiveness of both methods varied considerably between ecosystems. Point counts performed better in BFR than in CNP, detecting a greater percentage of known community richness (60% versus 41%) and generating more accurate species richness estimates. Conversely, mist netting performed better in CNP than in BFR, detecting a much higher percentage of known community richness (31% versus 7%). Indeed, mist netting proved overall to be highly ineffective within BFR. Best Akaike's Information Criterion models indicate differences in the effectiveness of methodologies between study sites relate to bird community composition, which in turn relates to ecological and biogeographical influences unique to each forest ecosystem. Results therefore suggest that, while generalized strengths and weaknesses of both methodologies can be defined, their overall effectiveness is also influenced by local characteristics specific to individual study sites. While this study focusses on ornithological surveys, the concept of local factors influencing effectiveness of field methodologies may also hold true for techniques targeting a wide range of taxonomic groups; this requires further research.

[Regional model of integrating occupational control over work condition into social hygienic monitoring system].

Existing practice implementing data obtained by occupational control and special evaluation of work conditions fails to evaluate hazardous effects caused in workers' health state by wide spectrum of risk factors such as social, ecologic, climate, etc. Widening possibilities for deeper health risk analysis can be provided by integration of laboratory and instrumental data on evaluation of hazardous and dangerous occupational factors into present systems of social hygienic monitoring. According to results of joint project within disciplinary program, Leningrad regional division of Federal Agency on sanitary epidemiologic supervision specified and implemented a regional model of integrated data base in informational funds of social hygienic monitoring. Consequently, quality and validity of management decisions in health risk factors control have significantly improved.i.

[The content of petroleum products, benzo(a)pyrene and heavy metals in soils of yamalnenets autonomous district and heavy metals in the hair of children].

The paper presents information about the content of benzo(a)pyrene in soil samples of petroleum products and the content of heavy metals (iron, copper, lead, arsenic, manganese, chromium, cadmium and mercury) in the soil and hair samples of children. Soil samples and hair were taken in October 2014 in the north-western part of the Yamal-Nenets Autonomous District. The values obtained were compared with the approximately permissible levels and maximum allowable concentrations adopted in the Russian Federation. Levels are determined compounds in the soil in general do not exceed the allowable concentrations. In hair samples there was noted marked exceeding of the recommended values for zinc, copper, chromium and iron 10%, 16.7%, 83.3% and 100% samples, respectively. The cause of the high iron content in the hair samples may be due to the quality of consumed water, which is characterized by low mineralization and high iron content. Increased chromium content of more than 80% of the hair samples can be caused, as in the case of iron, the quality of water consumed, but also a high proportion of local foods in the diet of people, rich by chromium. A conducted study on the state of the environment in the village, away from areas of hydrocarbon production, indicates to the low importance of anthropogenic impact.

Monitoring microbial diversity of bioreactors using metagenomic approaches.

With the rapid development of molecular techniques, particularly 'omics' technologies, the field of microbial ecology is growing rapidly. The applications of next generation sequencing have allowed researchers to produce massive amounts of genetic data on individual microbes, providing information about microbial communities and their interactions through in situ and in vitro measurements. The ability to identify novel microbes, functions, and enzymes, along with developing an understanding of microbial interactions and functions, is necessary for efficient production of useful and high value products in bioreactors. The ability to optimize bioreactors fully and understand microbial interactions and functions within these systems will establish highly efficient industrial processes for the production of bioproducts. This chapter will provide an overview of bioreactors and metagenomic technologies to help the reader understand microbial communities, interactions, and functions in bioreactors.

Shaping veterinary health policies in a global and evolving context.

National animal health policies have at their foundation the overarching need to address society's concerns about animal disease control, the welfare of animals and the safety and security of the animal production food supply. However, in today's global, complex and interdependent context, national animal health policies also impact a broader range of policy outcomes, ranging from public health protection through ecosystem health and biodiversity to the economic well-being and performance of many countries. As a result, there are several fundamentally important elements that must be considered in the elaboration of effective and relevant animal health policies. Policies must be (i) proportionate to the risk to be managed, (ii) transparent (to ensure easy understanding and implementation), and (iii) responsive to constantly evolving and changing hazards and risk pathways. In addition, it is critical that there are sufficient resources and capacity to implement the policies as well as incentives for compliance on the part of affected parties.