Effect of temperature and tree species on damage progression caused by whitespotted sawyer (Coleoptera: Cerambycidae) larvae in recently burned logs.

The whitespotted sawyer, Monochamus scutellatus scutellatus (Say) (Coleoptera: Ce-rambycidae), is one of the most damaging wood-boring insects in recently burned boreal forests of North America. In Canada, salvage logging after wildfire contributes to maintaining the timber volume required by the forest industry, but larvae of this insect cause significant damage that reduces the economic value of lumber products. This study aimed to estimate damage progression as a function of temperature in recently burned black spruce (Picea mariana (Miller) Britton, Sterns, and Poggenburg) and jack pine (Pinus banksiana Lambert) trees. Using axial tomographic technology, we modeled subcortical development and gallery depth progression rates as functions of temperature for both tree species. Generally, these rates were slightly faster in black spruce than in jack pine logs. Eggs laid on logs kept at 12 degrees C did not hatch or larvae were unable to establish themselves under the bark because no larval development was observed. At 16 degrees C, larvae stayed under the bark for > 200 d before penetrating into the sapwood. At 20 degrees C, half of the larvae entered the sapwood after 30-50 d, but gallery depth progression stopped for approximately 70 d, suggesting that larvae went into diapause. The other half of the larvae entered the sapwood only after 100-200 d. At 24 and 28 degrees C, larvae entered the sapwood after 26-27 and 21 d, respectively. At 28 degrees C, gallery depth progressed at a rate of 1.44 mm/d. Temperature threshold for subcortical development was slightly lower in black spruce (12.9 degrees C) than in jack pine (14.6 degrees C) and it was 1 degrees C warmer for gallery depth progression for both tree species. These results indicate that significant damage may occur within a few months after fire during warm summers, particularly in black spruce, which highlights the importance of beginning postfire salvage logging as soon as possible to reduce economic losses.

Predicting species diversity of benthic communities within turbid nearshore using full-waveform bathymetric LiDAR and machine learners.

Epi-macrobenthic species richness, abundance and composition are linked with type, assemblage and structural complexity of seabed habitat within coastal ecosystems. However, the evaluation of these habitats is highly hindered by limitations related to both waterborne surveys (slow acquisition, shallow water and low reactivity) and water clarity (turbid for most coastal areas). Substratum type/diversity and bathymetric features were elucidated using a supervised method applied to airborne bathymetric LiDAR waveforms over Saint-Siméon-Bonaventure's nearshore area (Gulf of Saint-Lawrence, Québec, Canada). High-resolution underwater photographs were taken at three hundred stations across an 8-km(2) study area. Seven models based upon state-of-the-art machine learning techniques such as Naïve Bayes, Regression Tree, Classification Tree, C 4.5, Random Forest, Support Vector Machine, and CN2 learners were tested for predicting eight epi-macrobenthic species diversity metrics as a function of the class number. The Random Forest outperformed other models with a three-discretized Simpson index applied to epi-macrobenthic communities, explaining 69% (Classification Accuracy) of its variability by mean bathymetry, time range and skewness derived from the LiDAR waveform. Corroborating marine ecological theory, areas with low Simpson epi-macrobenthic diversity responded to low water depths, high skewness and time range, whereas higher Simpson diversity relied upon deeper bottoms (correlated with stronger hydrodynamics) and low skewness and time range. The degree of species heterogeneity was therefore positively linked with the degree of the structural complexity of the benthic cover. This work underpins that fully exploited bathymetric LiDAR (not only bathymetrically derived by-products), coupled with proficient machine learner, is able to rapidly predict habitat characteristics at a spatial resolution relevant to epi-macrobenthos diversity, ranging from clear to turbid waters. This method might serve both to nurture marine ecological theory and to manage areas with high species heterogeneity where navigation is hazardous and water clarity opaque to passive optical sensors.

La loi de similitude / The similitude law

Le principe fondamental de l'homeopathie est la loi de Similitude: il est absolument incontournable. De quelle Similitude s'agit-il? Il s'agit de la Similitude entre: les symptomes provoques par l'ingestion d'une substance par un sujet sain et les symptomes releves chez un sujet malade. (AU)

China, remede du nouveau monde

Le Quinquina, encore appele China ou Cinchona, est un arbre de la famille des rubiacees. C'est l'ecorce qui en contient les principes actifs et qui est utilisee comme febrifuge depuis la decouverte de... (AU)

Synchronicite et idiosyncrasie / Synchronicity and idiosyncrasy

Il etait une fois, dans une maison bourgeoise, le chat Hector. Le chat avait l'habitude de sommeiller a cote d'un telephone, sur le fauteuil de la salle de sejour. A chaque fois que ce curieux... (AU)

Rosmarinus officinalis / Rosmarinus officinalis

Hahnemann parle du romarin dans Apothekerlexikon, sous la rubrique "Kranzrosmarin": "Romarin, rosmarinus officinalis, L, aux feuilles sessiles, arbuste a feuilles persistantes de l'Europe du sud et de la Suisse qui presente en mai et en juin des fleurs bleuatres, mais qui ne supporte pas de rester dehors pendant nos hivers. On a trouve une propriete d'excitant nervin, des vertus curatives dans la chlorose, l'hysterie et les catarrhes a ses feuilles et fleurs a l'odeur stimulante et a la saveur semblable..." Hahnemann parlait bien entendu de regions tres differentes de nos contrees mediterraneennes car, dans le Languedoc, le romarin persiste parfaitement toute l'annee dans les jardins et les garrigues