The potential to characterize ecological data with terrestrial laser scanning in Harvard Forest, MA

Contemporary terrestrial laser scanning (TLS) is being used widely in forest ecology applications to examine ecosystem properties at increasing spatial and temporal scales. Harvard Forest (HF) in Petersham, MA, USA, is a long-term ecological research (LTER) site, a National Ecological Observatory Network (NEON) location and contains a 35 ha plot which is part of Smithsonian Institution's Forest Global Earth Observatory (ForestGEO). The combination of long-term field plots, eddy flux towers and the detailed past historical records has made HF very appealing for a variety of remote sensing studies. Terrestrial laser scanners, including three pioneering research instruments: the Echidna Validation Instrument, the Dual-Wavelength Echidna Lidar and the Compact Biomass Lidar, have already been used both independently and in conjunction with airborne laser scanning data and forest census data to characterize forest dynamics. TLS approaches include three-dimensional reconstructions of a plot over time, establishing the impact of ice storm damage on forest canopy structure, and characterizing eastern hemlock (Tsuga canadensis) canopy health affected by an invasive insect, the hemlock woolly adelgid (Adelges tsugae). Efforts such as those deployed at HF are demonstrating the power of TLS as a tool for monitoring ecological dynamics, identifying emerging forest health issues, measuring forest biomass and capturing ecological data relevant to other disciplines. This paper highlights various aspects of the ForestGEO plot that are important to current TLS work, the potential for exchange between forest ecology and TLS, and emphasizes the strength of combining TLS data with long-term ecological field data to create emerging opportunities for scientific study.

Classifying ecosystems with metaproperties from terrestrial laser scanner data

In this study, we introduce metaproperty analysis of terrestrial laser scanner (TLS) data, and demonstrate its application through several ecological classification problems. Metaproperty analysis considers pulse level and spatial metrics derived from the hundreds of thousands to millions of lidar pulses present in a single scan from a typical contemporary instrument. In such large aggregations, properties of the populations of lidar data reflect attributes of the underlying ecological conditions of the ecosystems.In this study, we provide the Metaproperty Classification Model to employ TLS metaproperty analysis for classification problems in ecology. We applied this to a proof-of-concept study, which classified 88 scans from rooms and forests with 100% accuracy, to serve as a template.We then applied the Metaproperty Classification Model in earnest, to separate scans from temperate and tropical forests with 97.09% accuracy (N = 224), and to classify scans from inland and coastal tropical rainforests with 84.07% accuracy (N = 270).The results demonstrate the potential for metaproperty analysis to identify subtle and important ecosystem conditions, including diseases and anthropogenic disturbances. Metaproperty analysis serves as an augmentation to contemporary object reconstruction applications of TLS in ecology, and can characterize regional heterogeneity.

Supervised daily consumption, contingent take-home incentive and non-contingent take-home in methadone maintenance

Methadone maintenance therapy (MMT) has been found effective in treating heroin addiction. Serious consideration should be given to the modality of methadone distribution, as it influences not only treatment outcome but the attitudes of policy makers and the community, too. On one hand, the choice of take-home methadone removes the need for daily attendance at a methadone clinic, which seems to improve patients' quality of life. On the other, this method, because of its lack of supervision and the absence of strict consumption monitoring, runs the risk of methadone misuse and diversion. In this study, we compared A) supervised daily consumption, B) contingent take-home incentives and C) non-contingent take-home in methadone maintenance in three groups of heroin-addicted patients attending three different MMT programmes. Retention rates at 12 months were significantly higher in contingent take-home patients (group B) than in those with supervised daily consumption (group A) and the non-contingent take-home (group C). Retention rates were higher in group A than in group C patients. Compared to patients in groups A and B, those in group C showed fewer negative urinalyses and higher rates of self-reported diversion and episodes of crime or violence. Results indicate a more positive outcomes following take-home methadone associated with behavioural incentives and other measures that aim to facilitate treatment compliance than those following daily supervised consumption. By contrast, non-contingent take-home methadone given to non-stabilized patients is associated with a high rate of diversion, along with more crime episodes and maladaptive behaviours.

Long-acting opioid-agonists in the treatment of heroin addiction: why should we call them "substitution"?

Many studies have documented the safety, efficacy, and effectiveness of long-acting opioids (L-AOs), such as methadone and buprenorphine, in the treatment of heroin addiction. This article reviews the pharmacological differences between L-AO medications and short-acting opioids (heroin) in terms of reinforcing properties, pharmacokinetics, effects on the endocrine and immune systems. Given their specific pharmacological profile, L-AOs contribute to control addictive behavior, reduce craving, and restore the balance of disrupted endocrine function. The use of the term "substitution," referring to the fact that methadone or buprenorphine replace heroin in binding to brain opioid receptors, has been generalized to consider L-AOs as simple replacement of street drugs, thus contributing to the widespread misunderstanding of this treatment approach.