Scale for resource selection functions

Resource selection functions (RSFs) are statistical models defined to be proportional to the probability of use of a resource unit. My objective with this review is to identify how RSFs can be used to unravel the influence of scale in habitat selection. In wildlife habitat studies, including radiotelemetry, RSFs can be estimated using a variety of statistical methods, all of which can be used to explore the role of scale. All RSFs are bounded by the resolution of data and the spatial extent of the study area, but also allow predictor covariates to be measured at a variety of scales. Conditional logistic regression permits designs (e.g. matched case) that relate the process of habitat selection to a limited domain of resource units that might better characterize what is truly ‘available’ to the animal. Scale influences the process of habitat selection, e.g. food resources are often selected at fine spatial scales, whereas landscape patterns at much larger scales typically influence the location of home ranges. Scale also influences appropriate sampling in many ways: (1) heterogeneity might be obliterated (transmutation) if resolution or grain size is too large, (2) variance of habitat characteristics might be undersampled if extent or domain is too small, (3) timing and duration of observations can influence RSF models, and (d) both spatial and temporal autocorrelations can vary directly with the intensity of sampling. Using RSFs, researchers can examine habitat selection at multiple scales, and predictive models that bridge scales can be estimated. Using Geographical Information Systems, predictor covariates in RSF models can be measured at different scales easily so that the predictive ability of models at alternative spatial and temporal domains can be explored by the investigator. Identification of the scale that best explains the data can be evaluated by comparing alternative models using information‐theoretic metrics such as Akaike Information Criteria, and predictive capability of the models can be assessed using k‐fold cross validation.     

An analysis of the class of gene regulatory functions implied by a biochemical model

Understanding the integrated behavior of genetic regulatory networks, in which genes regulate one another's activities via RNA and protein products, is emerging as a dominant problem in systems biology. One widely studied class of models of such networks includes genes whose expression values assume Boolean values (i.e., on or off). Design decisions in the development of Boolean network models of gene regulatory systems include the topology of the network (including the distribution of input- and output-connectivity) and the class of Boolean functions used by each gene (e.g., canalizing functions, post functions, etc.). For example, evidence from simulations suggests that biologically realistic dynamics can be produced by scale-free network topologies with canalizing Boolean functions. This work seeks further insights into the design of Boolean network models through the construction and analysis of a class of models that include more concrete biochemical mechanisms than the usual abstract model, including genes and gene products, dimerization, cis-binding sites, promoters and repressors. In this model, it is assumed that the system consists of N genes, with each gene producing one protein product. Proteins may form complexes such as dimers, trimers, etc. The model also includes cis-binding sites to which proteins may bind to form activators or repressors. Binding affinities are based on structural complementarity between proteins and binding sites, with molecular binding sites modeled by bit-strings. Biochemically plausible gene expression rules are used to derive a Boolean regulatory function for each gene in the system. The result is a network model in which both topological features and Boolean functions arise as emergent properties of the interactions of components at the biochemical level. A highly biased set of Boolean functions is observed in simulations of networks of various sizes, suggesting a new characterization of the subset of Boolean functions that are likely to appear in gene regulatory networks.     

In silico identification and biochemical characterization of novel inhibitors of NQO1

From in silico docking and COMPARE analysis, novel inhibitors of human NAD(P)H quinone oxidoreductase (NQO1) have been identified from the NCI compound database, the most potent of which has an observed IC₅₀ of 0.7 μM. The inhibitors exhibit a diverse range of scaffolds. The ability of docking calculations to predict experimentally determined binding affinities for NQO1 is discussed, considering the influence of target flexibility and scoring function.     

Physiological Daily Inhalation Rates for Free-Living Pregnant and Lactating Adolescents and Women Aged 11 to 55 Years,Using Data from Doubly Labeled Water Measurements for Use in Health Risk Assessment

The distribution of physiological daily inhalation rates for pregnant and lactating females aged 11 to 55 years was determined according to total daily energy expenditures, energy costs for growth, pregnancy and lactation (maternal milk-energy synthesis and breast-energy output) in free-living females. Such published data were obtained using a methodology based on the disappearance rates of predetermined doses of doubly labeled water (²H₂O and H₂ ¹⁸O) in urine from non-pregnant and non-lactating females (n = 357), as well as saliva from gravid and breastfeeding females (n = 91), monitored by gas-isotope-ratio mass spectrometry over an aggregate period of about 6,000 days. Monte Carlo simulations were necessary to integrate total daily energy requirements of non-pregnant and non-lactating females into energy costs and weight changes at the 9th, 22nd, and 36th week of pregnancy and at the 6th and 27th, postpartum week: 540,000 data were simulated. The present article confirms that physiological daily inhalation rates for under-, normal-, and overweight/obese pregnant and lactating females expressed in m³/day and m³/kg-day are higher than those for males. For instance, in normal-weight subjects, inhalation rates are higher by 18 to 41% throughout pregnancy and 23 to 39% during postpartum weeks: actual values were higher in females by 1.13 to 2.01 m³/day at the 9th week of pregnancy, 3.74 to 4.53 m³/day at the 22nd week and 4.41 to 5.20 m³/day at the 36th week, and by 4.43 to 5.30 m³/day at the 6th postpartum week and 4.22 to 5.11 m³/day at the 27th postpartum week. The highest 99th percentiles were found to be 0.622 m³/kg-day in pregnant females and 0.647 m³/kg-day in lactating females. By comparison, the highest 99th percentile value for individuals aged 2.6 months to 96 years was determined to be 0.725 m³/kg-day in Brochu et al. (2006a) Brochu, P, Ducré-Robitaille, J F and Brodeur, J. 2006a. Physiological daily inhalation rates for free-living individuals aged 1 month to 96 years, using data from doubly labeled water measurements: a proposal for air quality criteria, standard calculations and health risk assessment. Hum Ecol Risk Assess, 12: 675–701. [CSA][Taylor & Francis Online], [Web of Science ®] [Google Scholar]. Air quality criteria and standard calculations based on the latter value for non-carcinogenic toxic compounds should therefore be protective for virtually all pregnant and lactating females. The present article highlights evidence that the current default assumption regarding the total daily air intake used by the Integrated Risk Information System (IRIS) to derive human equivalent concentrations in reference dose calculations is also underestimated compared to some higher 75th and 90th percentiles of physiological daily inhalation rates in pregnant and lactating females.     

Landscape assessment for sustainable planning

The 1st International Conference on Impact Assessment of Land Use Changes (IALUC) was held from the 6th to 9th of April 2008 at Humboldt University in Berlin, Germany. At the meeting, 160 oral presentations (including five plenary speeches) and 69 posters by representatives from 39 countries were presented. Papers and posters in four general sessions (Tools and Models, Policies and Scenarios, Scale and Indicators, and Participation and Socio-Economy) considered various aspects of the impact assessment of land use and landscape changes. This special section of the journal Ecological Indicators consists of nine selected presentations from different sub-sessions of the IALUC conference considering the use of indicators in landscape assessment.     

Stochastic inequality probabilities for adaptively randomized clinical trials

We examine stochastic inequality probabilities of the form P (X > Y) and P (X > max (Y, Z)) where X, Y, and Z are random variables with beta, gamma, or inverse gamma distributions. We discuss the applications of such inequality probabilities to adaptively randomized clinical trials as well as methods for calculating their values.     

The vitality model: A way to understand population survival and demographic heterogeneity

A four-parameter model describing mortality as the first passage of an abstract measure of survival capacity, vitality, is developed and used to explore four classic problems in demography: (1) medfly demographic paradox, (2) effect of diet restriction on longevity, (3) cross-life stage effects on survival curves and (4) mortality plateaus. The model quantifies the sources of mortality in these classical problems into vitality-dependent and independent parts, and characterizes the vitality-dependent part in terms of initial and evolving heterogeneities. Three temporal scales express the balance of these factors: a time scale of death from senescence, a time scale of accidental mortality and a crossover time between evolving vs. initial heterogeneity. The examples demonstrate how the first-passage approach provides a unique and informative perspective into the processes that shape the survival curves of populations.     

噬藻体研究进展

噬藻体（Cyanophage）是以蓝藻为寄主的浮游病毒类群,因其能特异性地感染蓝藻而具有重要的生态地位,是蓝藻＂水华＂潜在的控制因子。噬藻体的生物学、生态学特征是了解噬藻体的一扇窗,分子生物学研究仍将是主要的研究方向之一。同时,噬藻体研究手段也在不断更新。该文从这几个方面综述了噬藻体相关研究进展。     

Factors controlling the distribution of planktonic foraminifera in the Red Sea and implications for the development of transfer functions

The Red Sea is an extreme marine environment, with conditions limiting the application of standard geochemical proxies for the reconstruction of paleoclimate. In order to develop paleoenvironmental reconstruction methods which are not dependent on chemical signals, we investigated the distribution of planktonic foraminifera in the surface sediments and assessed the viability of constructing foraminiferal transfer functions in this basin. We find a distinct gradient in the faunal assemblage along the basin's axis, which is reflected in a high correlation between faunal composition and all considered environmental parameters (temperature, salinity, chlorophyll a concentration, stratification, and oxycline depth). As a result, transfer functions constructed by different methods (ANN, MAT, IKM, WA-PLS) appear to be able to estimate all of these parameters with a high average accuracy (15% of the parameter's range in the Red Sea). However, redundancy analysis of the distribution of foraminiferal assemblages in surface sediments alone did not yield unambiguous results in terms of which of the considered factors exerts a primary control on the foraminifera distribution and which of the observed relationships are the result of the mutual correlation among the environmental factors. To disentangle the effect of individual environmental parameters, we applied the obtained transfer functions on a newly generated Holocene record from the central Red Sea. The integration of published paleoclimate reconstructions with our data allowed us to identify productivity as the most likely primary control of the planktonic foraminifera distribution in the Red Sea. The generated transfer functions can estimate paleoproductivity with acceptable accuracy (RMSEP chlorophyll a = 0.1 mg/m³; ~ 8% of recent range), but only under such conditions in the past when circulation patterns and salinity levels in the basin were fundamentally comparable to the present day. Since productivity in the central and southern Red Sea is closely linked with the Monsoon-driven water exchange across the Strait of Bab al Mandab, the resulting reconstructions can provide indirect information on the mode and intensity of the monsoonal system in the past.