P. de Palacios

Variation in wood anatomical traits of Pinus sylvestris L. between Spanish regions of provenance

The Spanish populations of Pinus sylvestris L. occupy differentiated sites and must therefore include structural variations to cope with varied climate conditions. This study compares wood anatomical traits of P. sylvestris from ten Spanish regions of provenance with contrasting climates, taking into account the effects of region of provenance and tree nested within provenance on variation in wood biometry. In general, the effect of both sources of variation (provenance and tree) on wood biometry was highly significant. Most of the anatomical variations observed were intra-populational (at the tree level), although variation explained by provenance was high for some parameters (e.g., ray frequency and ray parenchyma cell frequency), suggesting high environmental influence. Trees in the driest region, growing in a Mediterranean phytoclimate, were characterized by large tracheid lumens, suggesting more efficient water conduction. They also had thick cell walls, which would reduce the risk of cavitation caused by high implosion stress during periods of drought, as well as a high ray tracheid frequency, implying greater water storage capacity in the sapwood. The population with greatest growth, located in an oroboreal phytoclimate, was characterized by large bordered pits and long tracheids, which would reduce resistivity in water transport. At higher altitudes, tracheid lumen diameter and resin canal diameter tended to be smaller, and intertracheid wall strength was greater. Results are discussed in relation to adaptation of the species to growth demands and frost.

Artificial neural networks in wood identification: the case of two Juniperus species from the Canary Islands.

Neural networks are complex mathematical structures inspired on biological neural networks, capable of learning from examples (training group) and extrapolating knowledge to an unknown sample (testing group). The similarity of wood structure in many species, particularly in the case of conifers, means that they cannot be differentiated using traditional methods. The use of neural networks can be an effective tool for identifying similar species with a high percentage of accuracy. This predictive method was used to differentiate Juniperus cedrus and J. phoenicea var. canariensis, both from the Canary Islands. The anatomical features of their wood are so similar that it is not possible to differentiate them using traditional methods. An artificial neural network was used to determine if this method could differentiate the two species with a high degree of probability through the biometry of their anatomy. To achieve the differentiation, a feedforward multilayer percepton network was designed, which attained 98.6% success in the training group and 92.0% success in the testing or unknown group. The proposed neural network is satisfactory for the desired purpose and enables J. cedrus and J. phoenicea var. canariensis to be differentiated with a 92% probability.

Abies pinsapo forests in Spain and Morocco: threats and conservation

The conifer forests of the Mediterranean Basin have been subjected to overuse by humans since ancient times. Some species have survived in inaccessible refuges but the ranges of other species have been greatly reduced by the effects of clearance for agriculture, livestock raising, illegal felling and, in some cases, fire. The firs are no exception and some now exist only as relict species. Abies pinsapo is an example, with the species surviving in only three enclaves in southern Spain and two in northern Morocco. Until the mid 20th century A. pinsapo forests were subject to major anthropogenic pressures, and in Spain they were under constant threat of overuse until they were acquired by the State. Conservation efforts have now, however, been undertaken in both Spain and Morocco, and the fact that all the A. pinsapo forests are covered by some form of protection preserves them from further inappropriate use or exploitation. These forests are now recovering after years of intensive grazing and use of their timber for construction, firewood and charcoal making. However, these relict forests face the new threats of climate change, arson and the appearance of pests. The limited area occupied by these forests makes them highly vulnerable to disturbance.

Estimating the Uncertainty of a Multilayer Perceptron Using the Monte Carlo Method

Artificial neural networks have become a powerful modeling tool. However, although they obtain an output with very good accuracy, they provide no information about the uncertainty of the network or its coverage intervals. This study describes the application of the Monte Carlo method to obtain the output uncertainty and coverage intervals of a particular type of artificial neural network: the multilayer perceptron.

Wood anatomy of the genus Abies a revieW

The literature on the wood anatomy of the genus Abies is reviewed and discussed, and complemented with a detailed study of 33 species, 1 subspecies and 4 varieties. In general, the species studied do not show diagnostic interspecific differences, although it is possible to establish differences between groups of species using certain quantitative and qualitative features.The marginal axial parenchyma consisting of single cells and the ray parenchyma cells with distinctly pitted horizontal walls, nodular end walls and presence of indentures are constant for the genus, although these features also occur in the other genera of the Abietoideae. The absence of ray tracheids in Abies can be used to distinguish it from Cedrus and Tsuga, and the irregularly shaped parenchymatous marginal ray cells are only shared with Cedrus. The absence of resin canals enables Abies to be distinguished from very closely related genera such as Keteleeria and Nothotsuga. The crystals in the ray cells, taxodioid cross-field pitting and the warty layer in the tracheids can be regarded as diagnostic generic features.

Key to the identification of conifer woods at the level of species. European and north american regions

This work presents the first step to establish a identification key of world-wide conifer woods at the species level. The identification of 120 coniferous species of North America and Europe have been established. Traditional methods of preparation and microscopic woods description have been followed. The 93 traits used were grouped in six main types: 29 characters of the tracheids, eight characters of the longitudinal parenchyma, 37 characters of wood rays, seven characters of resin ducts, two macroscopic characters, and 10 characters related to the geographical distribution of the species. An open key has been obtained for the identification of the species based on these six groups of traits. This work constitutes one of the research lines of the Wood Techonology Department of the ETSI Montes in Madrid, and can be used by researches and users devoted to the international woods trade of protected species.