Table_1_Does a Spruce Budworm Outbreak Affect the Growth Response of Black Spruce to a Subsequent Thinning?.DOCX

<p>In Canada, new forestry practices involving the natural dynamics of tree growth and regeneration are proposed for integrating forest management with biodiversity. In particular, the current spruce budworm [Choristoneura fumiferana (Clemens)] outbreak in northeastern North America is forcing natural resource managers to clarify the potential interactions between natural disturbances and commercial thinning. The aim of this study was to investigate if the spruce budworm outbreak of the 1970s affected the responses of black spruce [Picea mariana (Mill.) B.S.P.] to a subsequent thinning. Stem growth was reconstructed by measuring and cross-dating chronologies of tree-ring width of 1290 adult trees from 34 control and thinned stands within an area of 11,000 km² in the boreal forest of the Saguenay-Lac-Saint-Jean region (QC, Canada). The treatment consisted of a low thinning performed during 1995–1999 that removed 25–35% of the basal area. Segmented models were applied to the tree-ring chronologies to define the growth pattern during the outbreak and thinning periods within a time window of 8 years, representing the average duration of the effects of defoliation on growth. Trees showed abrupt growth decreases during the outbreak, with the tree-ring index showing minimum values in 1977–1979. The tree-ring index had a flat trend before thinning, while it increased for 6–10 years after thinning. The growth pattern during the outbreak period was characterized by a reduction, mainly in trees with larger tree rings, while slow-growing trees showed less sensitivity to the disturbance. Thinning produced a significant increase in tree growth. No relationship was found between the effects of spruce budworm outbreaks in trees and the changes in growth pattern after thinning. If the timespan between the two disturbances exceeds 7 years, partial cutting can be applied independently of the growth reductions that had occurred during the outbreak. When applied in black spruce stands with high annual radial growth, thinning is expected to optimize the volume growth of the residual trees.</p

Catalytic, Enantioselective Sulfenylation of Ketone-Derived Enoxysilanes

A catalytic, enantioselective, Lewis base-catalyzed α-sulfenylation of silyl enol ethers has been developed. To avoid acidic hydrolysis of the silyl enol ether substrates, a sulfenylating agent that did not require additional Brønsted acid activation, namely <i>N</i>-phenylthio­saccharin, was developed. Three classes of Lewis basestertiary amines, sulfides, and seleno­phosphor­amideswere identified as active catalysts for the α-sulfenylation reaction. Among a wide variety of chiral Lewis bases in all three classes, only chiral seleno­phosphor­amides afforded α-phenylthio ketones in generally high yield and with good enantio­selectivity. The selectivity of the reaction does not depend on the size of the silyl group but is highly sensitive to the double bond geometry and the bulk of the substituents on the double bond. The most selective substrates are those containing a geminal bulky substituent on the enoxy­silane. Computational analysis revealed that the enantio­selectivity arises from an intriguing interplay among sterically guided approach, distortion energy, and orbital interactions

Synchronization of the intra-ring variation of lumen diameter (LD) and sub-seasonal variation of water balance for the period 2010–2013.

<p>Open and solid dots indicate the LD of earlywood and latewood tracheids, respectively. Red line indicates the soil moisture for each studied year. Grey line indicates the average soil moisture for the last 30 years.</p

Standardized tracheidograms for the four years (2010–2013).

<p>The number of tracheids per ring was set to 25 and each standardize tracheidogram contains 16 tracheids in earlywood (Ew) and 9 in latewood (Lw). A) Lumen diameter (LD); B) Cell wall thickness (CWT); C) Ratio of LD to CWT (LD/CWT). The color lines represent the means and the shaded areas the 95% confidence intervals.</p

Temporal variation of different anatomical variables for the period 2010–2013.

<p>Anatomical variables: number of cells (nCells), number of earlywood tracheids (nEw), number of latewood tracheids (nLw), number of earlywood-like tracheids within the latewood (nIADFs), cell wall thickness of the earlywood (EwCWT) and lumen diameter of latewood (LwLD). Data are the means ± 2SE and different letters indicate significant differences between years.</p

Monthly temperature (°C) and precipitation (mm) for the period 2010–2013 from the closest meteorological station located in Figueira da Foz, at 25 km south from the study area.

<p>Monthly temperature (°C) and precipitation (mm) for the period 2010–2013 from the closest meteorological station located in Figueira da Foz, at 25 km south from the study area.</p

Mean temperature (T), annual precipitation (P), precipitation in September (Sep P) and soil moisture in March (Mar W), August (Aug W) and September (Sep W) for the long-term mean and for each studied year.

<p>Mean temperature (T), annual precipitation (P), precipitation in September (Sep P) and soil moisture in March (Mar W), August (Aug W) and September (Sep W) for the long-term mean and for each studied year.</p

Tree rings of <i>Pinus pinaster</i> for the period 2010–2013, with the ring produced in 2013 showing an intra-annual density fluctuation (IADF) in latewood.

<p>Tree rings of <i>Pinus pinaster</i> for the period 2010–2013, with the ring produced in 2013 showing an intra-annual density fluctuation (IADF) in latewood.</p

Geographic location of the study area in North America (A) and the experimental blocks (B).

<p>Geographic location of the study area in North America (A) and the experimental blocks (B).</p

Examples of the four growth patterns using the Schnute function.

<p>The discontinuous horizontal lines indicate the asymptotes (a). The thin discontinuous horizontal and vertical lines show the inflexion points (b). The black dots show the cumulative radial growth values for each study year and the continuous lines represent the model fitting.</p