A rapid staining-assisted wood sampling method for PCR-based detection of pine wood nematode Bursaphelenchus xylophilus in Pinus massoniana wood tissue

For reasons of unequal distribution of more than one nematode species in wood, and limited availability of wood samples required for the PCR-based method for detecting pinewood nematodes in wood tissue of Pinus massoniana, a rapid staining-assisted wood sampling method aiding PCR-based detection of the pine wood nematode Bursaphelenchus xylophilus (Bx) in small wood samples of P. massoniana was developed in this study. This comprised a series of new techniques: sampling, mass estimations of nematodes using staining techniques, and lowest limit Bx nematode mass determination for PCR detection. The procedure was undertaken on three adjoining 5-mg wood cross-sections, of 0.5 · 0.5 · 0.015 cm dimension, that were cut from a wood sample of 0.5 · 0.5 · 0.5 cm initially, then the larger wood sample was stained by acid fuchsin, from which two 5-mg wood cross-sections (that adjoined the three 5-mg wood cross-sections, mentioned above) were cut. Nematode-staining-spots (NSSs) in each of the two stained sections were counted under a microscope at 100· magnification. If there were eight or more NSSs present, the adjoining three sections were used for PCR assays. The B. xylophilus – specific amplicon of 403 bp (DQ855275) was generated by PCR assay from 100.00% of 5-mg wood cross-sections that contained more than eight Bx NSSs by the PCR assay. The entire sampling procedure took only 10 min indicating that it is suitable for the fast estimation of nematode numbers in the wood of P. massonina as the prelimary sample selections for other more expensive Bx-detection methods such as PCR assay.

Assessing the role of Mediterranean evergreen oaks canopy cover in land surface albedo and temperature using a remote sensing-based approach

Modifications in vegetation cover can have an impact on the climate through changes in biogeochemical and biogeophysical processes. In this paper, the tree canopy cover percentage of a savannah-like ecosystem (montado/dehesa) was estimated at Landsat pixel level for 2011, and the role of different canopy cover percentages on land surface albedo (LSA) and land surface temperature (LST) were analysed. A modelling procedure using a SGB machine-learning algorithm and Landsat 5-TM spectral bands and derived vegetation indices as explanatory variables, showed that the estimation of montado canopy cover was obtained with good agreement (R2 = 78.4%). Overall, montado canopy cover estimations showed that low canopy cover class (MT_1) is the most representative with 50.63% of total montado area. MODIS LSA and LST products were used to investigate the magnitude of differences in mean annual LSA and LST values between contrasting montado canopy cover percentages. As a result, it was found a significant statistical relationship between montado canopy cover percentage and mean annual surface albedo (R2 = 0.866, p < 0.001) and surface temperature (R2 = 0.942, p < 0.001). The comparisons between the four contrasting montado canopy cover classes showed marked differences in LSA (χ2 = 192.17, df = 3, p < 0.001) and LST (χ2 = 318.18, df = 3, p < 0.001). The highest montado canopy cover percentage (MT_4) generally had lower albedo than lowest canopy cover class, presenting a difference of −11.2% in mean annual albedo values. It was also showed that MT_4 and MT_3 are the cooler canopy cover classes, and MT_2 and MT_1 the warmer, where MT_1 class had a difference of 3.42 °C compared with MT_4 class. Overall, this research highlighted the role that potential changes in montado canopy cover may play in local land surface albedo and temperature variations, as an increase in these two biogeophysical parameters may potentially bring about, in the long term, local/regional climatic changes moving towards greater aridity.