Human versus animal: contrasting decomposition dynamics of mammalian analogues in experimental taphonomy

Taphonomic studies regularly employ animal analogues for human decomposition due to ethical restrictions relating to the use of human tissue. However, the validity of using animal analogues in soil decomposition studies is still questioned. This study compared the decomposition of skeletal muscle tissues (SMTs) from human (Homo sapiens), pork (Sus scrofa), beef (Bos taurus), and lamb (Ovis aries) interred in soil microcosms. Fixed interval samples were collected from the SMT for microbial activity and mass tissue loss determination; samples were also taken from the underlying soil for pH, electrical conductivity, and nutrient (potassium, phosphate, ammonium, and nitrate) analysis. The overall patterns of nutrient fluxes and chemical changes in nonhuman SMT and the underlying soil followed that of human SMT. Ovine tissue was the most similar to human tissue in many of the measured parameters. Although no single analogue was a precise predictor of human decomposition in soil, all models offered close approximations in decomposition dynamics.

Managing the complexity of information flow for construction small and medium-sized enterprises (CSMEs) using system dynamics and collaborative technologies

With the increase in e-commerce and the digitisation of design data and information,the construction sector has become reliant upon IT infrastructure and systems. The design and production process is more complex, more interconnected, and reliant upon greater information mobility, with seamless exchange of data and information in real time. Construction small and medium-sized enterprises (CSMEs), in particular,the speciality contractors, can effectively utilise cost-effective collaboration-enabling technologies, such as cloud computing, to help in the effective transfer of information and data to improve productivity. The system dynamics (SD) approach offers a perspective and tools to enable a better understanding of the dynamics of complex systems. This research focuses upon system dynamics methodology as a modelling and analysis tool in order to understand and identify the key drivers in the absorption of cloud computing for CSMEs. The aim of this paper is to determine how the use of system dynamics (SD) can improve the management of information flow through collaborative technologies leading to improved productivity. The data supporting the use of system dynamics was obtained through a pilot study consisting of questionnaires and interviews from five CSMEs in the UK house-building sector.

Is behavioral ecology important for understanding and predicting population dynamics?

Population ecology is a discipline that studies changes in the number and composition (age, sex) of the individuals that form a population. Many of the mechanisms that generate these changes are associated with individual behavior, for example how individuals defend their territories, find mates or disperse. Therefore, it is important to model population dynamics considering the potential influence of behavior on the modeled dynamics. This study illustrates the diversity of behaviors that influence population dynamics describing several methods that allow integrating behavior into population models and range from simpler models that only consider the number of individuals to complex individual-based models that capture great levels of detail. A series of examples shows the importance of explicitly considering behavior in population modeling to avoid reaching erroneous conclusions. This integration is particularly relevant for conservation, as incorrect predictions regarding the dynamics of populations of conservation interest can lead to inadequate assessment and management. Improved predictions can favor effective protection of species and better use of the limited financial and human conservation resources.

Using Distributed Temperature Sensing to monitor field scale dynamics of ground surface temperature and related substrate heat flux

We present one of the first studies of the use of Distributed Temperature Sensing (DTS) along fibre-optic cables to purposely monitor spatial and temporal variations in ground surface temperature (GST) and soil temperature, and provide an estimate of the heat flux at the base of the canopy layer and in the soil. Our field site was at a groundwater-fed wet meadow in the Netherlands covered by a canopy layer (between 0-0.5 m thickness) consisting of grass and sedges. At this site, we ran a single cable across the surface in parallel 40 m sections spaced by 2 m, to create a 40×40 m monitoring field for GST. We also buried a short length (≈10 m) of cable to depth of 0.1±0.02 m to measure soil temperature. We monitored the temperature along the entire cable continuously over a two-day period and captured the diurnal course of GST, and how it was affected by rainfall and canopy structure. The diurnal GST range, as observed by the DTS system, varied between 20.94 and 35.08◦C; precipitation events acted to suppress the range of GST. The spatial distribution of GST correlated with canopy vegetation height during both day and night. Using estimates of thermal inertia, combined with a harmonic analysis of GST and soil temperature, substrate and soil-heat fluxes were determined. Our observations demonstrate how the use of DTS shows great promise in better characterising area-average substrate/soil heat flux, their spatiotemporal variability, and how this variability is affected by canopy structure. The DTS system is able to provide a much richer data set than could be obtained from point temperature sensors. Furthermore, substrate heat fluxes derived from GST measurements may be able to provide improved closure of the land surface energy balance in micrometeorological field studies. This will enhance our understanding of how hydrometeorological processes interact with near-surface heat fluxes.

Spatio-temporal variability of polynya dynamics and ice production in the Laptev Sea between the winters of 1979/80 and 2007/08

Polynyas in the Laptev Sea are examined with respect to recurrence and interannual wintertime ice production.We use a polynya classification method based on passive microwave satellite data to derive daily polynya area from long-term sea-ice concentrations. This provides insight into the spatial and temporal variability of open-water and thin-ice regions on the Laptev Sea Shelf. Using thermal infrared satellite data to derive an empirical thin-ice distribution within the thickness range from 0 to 20 cm, we calculate daily average surface heat loss and the resulting wintertime ice formation within the Laptev Sea polynyas between 1979 and 2008 using reanalysis data supplied by the National Centers for Environmental Prediction, USA, as atmospheric forcing. Results indicate that previous studies significantly overestimate the contribution of polynyas to the ice production in the Laptev Sea. Average wintertime ice production in polynyas amounts to approximately 55 km39 27% and is mostly determined by the polynya area, wind speed and associated large-scale circulation patterns. No trend in ice production could be detected in the period from 1979/80 to 2007/08.

A cautionary note on the use of Ornstein Uhlenbeck models in macroevolutionary studies

Phylogenetic comparative methods are increasingly used to give new insights into the dynamics of trait evolution in deep time. For continuous traits the core of these methods is a suite of models that attempt to capture evolutionary patterns by extending the Brownian constant variance model. However, the properties of these models are often poorly understood, which can lead to the misinterpretation of results. Here we focus on one of these models – the Ornstein Uhlenbeck (OU) model. We show that the OU model is frequently incorrectly favoured over simpler models when using Likelihood ratio tests, and that many studies fitting this model use datasets that are small and prone to this problem. We also show that very small amounts of error in datasets can have profound effects on the inferences derived from OU models. Our results suggest that simulating fitted models and comparing with empirical results is critical when fitting OU and other extensions of the Brownian model. We conclude by making recommendations for best practice in fitting OU models in phylogenetic comparative analyses, and for interpreting the parameters of the OU model.

The biogeophysical climatic impacts of anthropogenic land use change during the Holocene

The first agricultural societies were established around 10 ka BP and had spread across much of Europe and southern Asia by 5.5 ka BP with resultant anthropogenic deforestation for crop and pasture land. Various studies (e.g. Joos et al., 2004; Kaplan et al., 2011; Mitchell et al., 2013) have attempted to assess the biogeochemical implications for Holocene climate in terms of increased carbon dioxide and methane emissions. However, less work has been done to examine the biogeophysical impacts of this early land use change. In this study, global climate model simulations with Hadley Centre Coupled Model version 3 (HadCM3) were used to examine the biogeophysical effects of Holocene land cover change on climate, both globally and regionally, from the early Holocene (8 ka BP) to the early industrial era (1850 CE). Two experiments were performed with alternative descriptions of past vegetation: (i) one in which potential natural vegetation was simulated by Top-down Representation of Interactive Foliage and Flora Including Dynamics (TRIFFID) but without land use changes and (ii) one where the anthropogenic land use model Kaplan and Krumhardt 2010 (KK10; Kaplan et al., 2009, 2011) was used to set the HadCM3 crop regions. Snapshot simulations were run at 1000-year intervals to examine when the first signature of anthropogenic climate change can be detected both regionally, in the areas of land use change, and globally. Results from our model simulations indicate that in regions of early land disturbance such as Europe and south-east Asia detectable temperature changes, outside the normal range of variability, are encountered in the model as early as 7 ka BP in the June–July–August (JJA) season and throughout the entire annual cycle by 2–3 ka BP. Areas outside the regions of land disturbance are also affected, with virtually the whole globe experiencing significant temperature changes (predominantly cooling) by the early industrial period. The global annual mean temperature anomalies found in our single model simulations were −0.22 at 1850 CE, −0.11 at 2 ka BP, and −0.03 °C at 7 ka BP. Regionally, the largest temperature changes were in Europe with anomalies of −0.83 at 1850 CE, −0.58 at 2 ka BP, and −0.24 °C at 7 ka BP. Large-scale precipitation features such as the Indian monsoon, the Intertropical Convergence Zone (ITCZ), and the North Atlantic storm track are also impacted by local land use and remote teleconnections. We investigated how advection by surface winds, mean sea level pressure (MSLP) anomalies, and tropospheric stationary wave train disturbances in the mid- to high latitudes led to remote teleconnections.

In the mood: the dynamics of collective sentiments on Twitter

We study the relationship between the sentiment levels of Twitter users and the evolving network structure that the users created by @-mentioning each other. We use a large dataset of tweets to which we apply three sentiment scoring algorithms, including the open source SentiStrength program. Specifically we make three contributions. Firstly we find that people who have potentially the largest communication reach (according to a dynamic centrality measure) use sentiment differently than the average user: for example they use positive sentiment more often and negative sentiment less often. Secondly we find that when we follow structurally stable Twitter communities over a period of months, their sentiment levels are also stable, and sudden changes in community sentiment from one day to the next can in most cases be traced to external events affecting the community. Thirdly, based on our findings, we create and calibrate a simple agent-based model that is capable of reproducing measures of emotive response comparable to those obtained from our empirical dataset.

The timing of Neotropical speciation dynamics: A reconstruction of Myiopagis flycatcher diversification using phylogenetic and paleogeographic data

Neotropical forests have brought forth a large proportion of the world`s terrestrial biodiversity, but the underlying evolutionary mechanisms and their timing require further elucidation. Despite insights gained from phylogenetic studies, uncertainties about molecular clock rates have hindered efforts to determine the timing of diversification processes. Moreover, most molecular research has been detached from the extensive body of data on Neotropical geology and paleogeography. We here examine phylogenetic relationships and the timing of speciation events in a Neotropical flycatcher genus (Myiopagis) by using calibrations from modern geologic data in conjunction with a number of recently developed DNA sequence dating algorithms and by comparing these estimates with those based on a range of previously proposed molecular clock rates. We present a well-supported hypothesis of systematic relationships within the genus. Our age estimates of Myiopagis speciation events based on paleogeographic data are in close agreement with nodal ages derived from a ""traditional"" avian mitochondrial 2%/My clock, while contradicting other clock rates. Our comparative approach corroborates the consistency of the traditional avian mitochondrial clock rate of 2%/My for tyrant-flycatchers. Nevertheless, our results argue against the indiscriminate use of molecular clock rates in evolutionary research and advocate the verification of the appropriateness of the traditional clock rate by means of independent calibrations in individual studies. (C) 2009 Elsevier Inc. All rights reserved.

Dynamics of Dissolved Forms of Carbon and Inorganic Nitrogen in Small Watersheds of the Coastal Atlantic Forest in Southeast Brazil

Based on the fact that streamwater quality reflects landscape conditions, the objectives of this study were: to investigate nitrogen (N), carbon (C), and major ion concentrations in six streams crossing minimally disturbed Atlantic Forest areas, with similar geomorphological characteristics; to determine N and C fluxes in one of these pristine streams (Indaia); and assess the impact of human activity on the biogeochemistry of two other streams in the same region, crossing urbanized areas. The distribution pattern of carbon and inorganic nitrogen dissolved forms, as well as the major ion and biogenic gas concentrations in the streamwater, was similar in pristine streams, indicating that the C and N dynamics were determined by influence of some factors, such as climate, atmospheric deposition, geology, soil type, and land covering, which were analogous in the forested watersheds. The urban streams were significantly different from the pristine streams, showing low dissolved oxygen concentrations, high respiration rates, and high concentrations of carbon dioxide, dissolved inorganic nitrogen, dissolved inorganic carbon, and major ion. These differences were attributed to anthropogenic impact on water quality, especially domestic sewage discharge. Additionally, in the Indaia stream, it was possible to observe the importance of rainfall over temporal dynamics of dissolved carbon forms, and also, the obtained specific flux of dissolved inorganic nitrogen was relatively elevated (approximately 11 kg ha(-1) year(-1)). These results reveal the influence of human activity over the biogeochemistry of coastal streams and also indicate the importance N export of Atlantic Forest to the ocean.

Predator-prey models: an application for the plankton dynamics of lake Geneva

In this paper we present a hierarchical Bayesian analysis for a predator-prey model applied to ecology considering the use of Markov Chain Monte Carlo methods. We consider the introduction of a random effect in the model and the presence of a covariate vector. An application to ecology is considered using a data set related to the plankton dynamics of lake Geneva for the year 1990. We also discuss some aspects of discrimination of the proposed models.

Combined Crystallographic and Solution Molecular Dynamics Study of Allosteric Effects in Ester and Ketone p-tert-Butylcalix[4]arene Derivatives and Their Complexes with Acetonitrile, Cd(II), and Pb(II)

We describe here a procedure to bridge the gap in the field of calixarene physicochemistry between solid-state atomic-resolution structural information and the liquid-state low-resolution thermodynamics and spectroscopic data. We use MD simulations to study the kinetics and energetics involved in the complexation of lower rim calix[4]arene derivatives (L), containing bidentate ester (1) and ketone (2) pendant groups, with acetonitrile molecule (MeCN) and Cd2+ and Pb2+ ions (M2+) in acetonitrile solution. On one hand, we found that the prior inclusion of MeCN into the calix to form a L(MeCN) adduct has only a weak effect in preorganizing the hydrophilic cavity toward metal ion binding. On the other hand, the strong ion-hydrophilic cavity interaction produces a wide open calix which enhances the binding of one MeCN molecule (allosteric effect) to stabilize the whole (M2+)1(MeCN) bifunctional complex. We reach two major conclusions: (i) the MD results for the (M2+)1(MeCN) binding are in close agreement with the ""endo"", fully encapsulated, metal complex found by X-ray diffraction and in vacuo MD calculations, and (ii) the MD structure for the more flexible 2 ligand, however, differs from the also endo solid-state molecule. In fact, it shows strong solvation effects at the calixarene lower bore by competing MeCN molecules that share the metal coordination sphere with the four C=O oxygens of an ""exo"" (M2+)2(MeCN) complex.

A study of the relaxation dynamics in a quadrupolar NMR system using Quantum State Tomography

This article reports a relaxation study in an oriented system containing spin 3/2 nuclei using quantum state tomography (QST). The use of QST allowed evaluating the time evolution of all density matrix elements starting from several initial states. Using an appropriated treatment based on the Redfield theory, the relaxation rate of each density matrix element was measured and the reduced spectral densities that describe the system relaxation were determined. All the experimental data could be well described assuming pure quadrupolar relaxation and reduced spectral densities corresponding to a superposition of slow and fast motions. The data were also analyzed in the context of Quantum Information Processing, where the coherence loss of each qubit of the system was determined using the partial trace operation. (C) 2008 Elsevier Inc. All rights reserved.

Structure, Dynamics, and RNA Interaction Analysis of the Human SBDS Protein

Shwachman-Bodian-Diamond syndrome is an autosomal recessive genetic syndrome with pleiotropic phenotypes, including pancreatic deficiencies, bone marrow dysfunctions with increased risk of myelodysplasia or leukemia, and skeletal abnormalities. This syndrome has been associated with mutations in the SBDS gene, which encodes a conserved protein showing orthologs in Archaea and eukaryotes. The Shwachman-Bodian-Diamond syndrome pleiotropic phenotypes may be an indication of different cell type requirements for a fully functional SBDS protein. RNA-binding activity has been predicted for archaeal and yeast SBDS orthologs, with the latter also being implicated in ribosome biogenesis. However, full-length SBDS orthologs function in a species-specific manner, indicating that the knowledge obtained from model systems may be of limited use in understanding major unresolved issues regarding SBDS function, namely, the effect of mutations in human SBDS on its biochemical function and the specificity of RNA interaction. We determined the solution structure and backbone dynamics of the human SBDS protein and describe its RNA binding site using NMR spectroscopy. Similarly to the crystal structures of Archaea, the overall structure of human SBDS comprises three well-folded domains. However, significant conformational exchange was observed in NMR dynamics experiments for the flexible linker between the N-terminal domain and the central domain, and these experiments also reflect the relative motions of the domains. RNA titrations monitored by heteronuclear correlation experiments and chemical shift mapping analysis identified a classic RNA binding site at the N-terminal FYSH (fungal, Yhr087wp, Shwachman) domain that concentrates most of the mutations described for the human SBDS. (C) 2010 Elsevier Ltd. All rights reserved.