Multilevel Latent Gaussian Process Model for Mixed Discrete and Continuous Multivariate Response Data

We propose a Bayesian model for mixed ordinal and continuous multivariate data to evaluate a latent spatial Gaussian process. Our proposed model can be used in many contexts where mixed continuous and discrete multivariate responses are observed in an effort to quantify an unobservable continuous measurement. In our example, the latent, or unobservable measurement is wetland condition. While predicted values of the latent wetland condition variable produced by the model at each location do not hold any intrinsic value, the relative magnitudes of the wetland condition values are of interest. In addition, by including point-referenced covariates in the model, we are able to make predictions at new locations for both the latent random variable and the multivariate response. Lastly, the model produces ranks of the multivariate responses in relation to the unobserved latent random field. This is an important result as it allows us to determine which response variables are most closely correlated with the latent variable. Our approach offers an alternative to traditional indices based on best professional judgment that are frequently used in ecology. We apply our model to assess wetland condition in the North Platte and Rio Grande River Basins in Colorado. The model facilitates a comparison of wetland condition at multiple locations and ranks the importance of in-field measurements.     

Rapid phase adjustment of melatonin and core body temperature rhythms following a 6-h advance of the light/dark cycle in the horse

Background  

Rapid displacement across multiple time zones results in a conflict between the new cycle of light and dark and the previously entrained program of the internal circadian clock, a phenomenon known as jet lag. In humans, jet lag is often characterized by malaise, appetite loss, fatigue, disturbed sleep and performance deficit, the consequences of which are of particular concern to athletes hoping to perform optimally at an international destination. As a species renowned for its capacity for athletic performance, the consequences of jet lag are also relevant for the horse. However, the duration and severity of jet lag related circadian disruption is presently unknown in this species. We investigated the rates of re-entrainment of serum melatonin and core body temperature (BT) rhythms following an abrupt 6-h phase advance of the LD cycle in the horse.     

Response of a red clone of Myzus persicae (Hemiptera: Aphididae) to sublethal concentrations of imidacloprid in the laboratory and greenhouse

BACKGROUND: Pest resurgence following a pesticide application may occur owing to a stimulatory (hormetic) response to sublethal insecticide concentrations. The objective of the present study was to examine the potential for a greenhouse‐derived red clone of Myzus persicae to exhibit resurgence owing to a hormetic response following a systemic imidacloprid treatment in a bell pepper greenhouse. RESULTS: No differences in mortality and fecundity were observed among apterous adults exposed to sublethal imidacloprid concentrations on excised pepper leaves fed aqueous solutions of imidacloprid. Survival of first‐generation progeny was negatively affected by imidacloprid exposure, yet surviving progeny exhibited no differences in development rates or fecundity from progeny of adults unexposed to imidacloprid. Aphid mortality declined most rapidly in clip cages on pepper leaves at the top of the pepper canopy as compared with leaves present at the middle or bottom of the pepper canopy. CONCLUSION: Imidacloprid decays rapidly in mature pepper plants, resulting in sublethal concentrations in the upper canopy in as little as 4 weeks. Sublethal insecticide concentrations have been implicated in the resurgence of pest populations; however, exposure to sublethal doses of imidacloprid are unlikely to result in pesticide‐induced resurgence of the M. persicae aphid clone examined in this study. Copyright © 2011 Society of Chemical Industry     

The BIOEXPLOIT Project

The EU Framework 6 Integrated Project BIOEXPLOIT concerns the exploitation of natural plant biodiversity for the pesticide-free production of food. It focuses on the pathogens Phytophthora infestans, Septoria tritici, Blumeria graminis, Puccinia spp. and Fusarium spp. and on the crops wheat, barley, tomato and potato. The project commenced in October 2005, comprises 45 laboratories in 12 countries, and is carried out by partners from research institutes, universities, private companies and small-medium enterprises. The project has four strategic objectives covered in eight sub-projects. These objectives relate to (i) understanding the molecular components involved in durable disease resistance, (ii) exploring and exploiting the natural biodiversity in disease resistance, (iii) accelerating the introduction of marker-assisted breeding and genetic engineering in the EU plant breeding industry, and (iv) coordinating and integrating resistance breeding research, providing training in new technologies, disseminating the results, and transferring knowledge and technologies to the industry.     

Comparative Advantages of Small-Scale Forestry Among Emerging Forest Tenures

Forestland tenure institutions and patterns are in a period of rapid change in the USA. Historically dominant forestland tenures are disappearing, and new tenures are emerging. Traditional, vertically integrated forest products firms have shed their forestland holdings which have been picked up by Timber Investment Management Organizations (TIMOs) and Real Estate Investment Trusts (REITs). Increasing numbers of private individuals and families are purchasing small rural tracts and some communities are developing innovative means to gain control over nearby forestlands in order to protect these lands from commercial real estate development. Within this context of rapid ownership change, small-scale forest owners including families and communities find themselves at a competitive disadvantage, relative to large corporate owners, in wood commodity markets. This paper considers how small-scale forest tenures, relative to large corporate tenures, may be advantageous to society with regard to selected ecological, social, and economic factors. While the paper primarily draws upon illustrations from the US Pacific Northwest, its themes are global in nature.     

Dynamic riparian buffer widths from potential non-point source pollution areas in forested watersheds

Efforts to manage National Forests in the USA for wood production, while protecting water quality, are currently constrained by models that do not address the temporal dynamics of variable non-point source (NPS) areas. NPS areas are diffuse sources of contaminants contributed mostly by runoff as a result of different land use activities. Riparian vegetative buffers are often used to control contaminants from NPS areas but defining suitable widths require different policy considerations. In this study, the approach for defining suitable buffer widths is to apply a distributed process-based model that predicts potential NPS areas prone to generating runoff in relation to overland flow distances. A case study of the concept was applied to the 72 km² Pete King watershed located in the Clearwater National Forest (CNF) in central Idaho, USA. This grid modeling approach is based on a Geographic Information System (GIS) and it integrates the soil moisture routing (SMR) model with probabilistic analysis. The SMR model is a daily water balance model that simulates the hydrology of forested watersheds using real or stochastically generated climate data, a digital elevation model, soil, and land use data. The probabilistic analysis incorporates the variability of soil depth and accounts for uncertainties associated with the prediction of NPS areas using Monte Carlo simulation. A 1-year simulation for the case study location was performed to examine the spatial and temporal changes in NPS areas prone to generating runoff. The results of the simulation indicate that the seasonal variability of saturated areas determines the spatial dynamics of the potential NPS pollution. Use of this model for the design of riparian buffer widths would increase the effectiveness of decision-making in forest management and planning by mapping or delineating NPS areas likely to transport contaminants to perennial surface water bodies.     

Finding the appropriate level of complexity for a simulation model: An example with a forest growth model

The topic of model complexity is fundamental to model developers and model users. In this study, we investigate how over- and under-fitting of a driving function in a simulation model influences the predictive ability of the model. Secondly, we investigate whether model selection approaches succeed in selecting driving functions with the best predictive ability. We address these issues through an example with the forest simulator SORTIE-ND. Utilizing maximum likelihood methods and individual tree growth data we parameterize five growth functions of increasing complexity. We then incorporate each growth function into the simulation model SORTIE-ND and test predicted growth against independent data. Compared to the independent data, the simplest and the most complex growth functions had the poorest predictive ability while functions of intermediate complexity had the best predictive ability. The poor predictive ability of the simplest model is caused by poor approximation of the system while the poor predictive ability of the most complex model is caused by biased parameter estimates. A growth function of intermediate complexity was the most parsimonious model where error due to approximation and error due to estimation were simultaneously minimized. The model selection criteria AIC and BIC were found to select complex functions that were over-fitted according to the independent data comparison. BIC was closer to choosing the model that minimized prediction error than AIC. In this example, BIC is the more appropriate model selection criterion. It is important that both model developers and models users remember that more complex models do not always result in better predictive models.     

Effects of fluid therapy on total protein and its influence on calculated unmeasured anions in the anesthetized dog

Objective – To determine the effects of IV lactated Ringer's solution at a rate of 10 mL/kg/h in anesthetized dogs on total protein (TP) measurement and calculation of unmeasured anions (UAs) using 2 quantitative methods of acid‐base status determination, strong ion gap, and modified base deficit. Design – Prospective clinical study. Animals – Forty‐three dogs, anesthetic health status I or II according to the American Society of Anesthesiologists, undergoing surgery under general anesthesia. Interventions – Arterial blood analyses for gas tensions, acid‐base balance, electrolytes, lactate, hemoglobin (Hb), PCV, and TP were performed under general anesthesia immediately after induction and again after administration of approximately 10 mL/kg of lactated Ringer's solution (given over 1 h). UAs were determined using strong ion gap and modified base deficit. Measurements and Main Results – Fluid replacement for 1 hour decreased TP, Hb, and PCV by 8%, 7.8%, and 8.6%, respectively. The degree of decrease in TP did not impact the calculation of UAs by quantitative methods when the prefluid administration TP value was used instead of the postfluid TP value in the calculation. Comparison of the two methods showed a low correlation (r≤0.68) and marked differences in the precision (1.96 SD). Conclusions: The degree of decrease in TP after 1 hour of fluid replacement at approximately 10 mL/kg does not affect determination of UAs when prefluid TP is used within that time period.