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The present study focused on the analysis of the structure of the Anogeissus leiocarpa dominated natural stands in the Wari-Maro forest reserve which are under high and minimal anthropogenic pressures. These stands were considered for forest inventories after carrying out a random sampling scheme of 40 sample units of 30 m × 50 m. In each level pressure stand, the dbh and tree-height of identified tree-species were measured in each plot. Data analyses were based on the computation of structural parameters, establishment of diameter and height distributions and the floristic composition of the two types of stands. Results obtained showed higher values for the overall basal area (9.78 m2 ha−1), mean height (22.37 m) and mean diameter (36.92 cm) for A. leiocarpa in low-pressure stands. In high-pressure stands, some species like Afzelia africana had lower Importance Value Index and the frequency of A. leiocarpa trees in the successive diameter classes dropped rapidly and the value of the logarithmic slope of the height–diameter relationship was lower (9.77) indicating a lanky shape. Results obtained suggest that effective conservation is needed for A. leiocarpa stands under high pressure by limiting human interference and developing appropriate strategy for restoration purposes. [ABSTRACT FROM AUTHOR]

Forest structural diversity was estimated for an ecological province in the north-central region of the United States of America using data for nearly 350 000 trees observed on >12 000 forest inventory plots. Each plot was 672 m2 in area, and the sampling intensity was approximately 1 plot/2400 ha. Two indices were used for each of two commonly and accurately measured inventory variables: species count and the Shannon index for tree species and standard deviation and the Shannon index for tree diameter. The primary results of the study were fourfold: (i) ranges of spatial correlation for diversity indices were small, on the order of 5–10 km, (ii) high proportions of provincewide diversity were realized for circular areas with radii as small as 15 km, (iii) diversity for both species and diameter exhibited strong northwest to southeast spatial patterns, and (iv) plot-level α diameter diversity was highly correlated with mean plot-level tree diameter. La diversité structurale de la forêt a été estimée dans une province écologique du centre-nord des tats-Unis d’Amérique en utilisant les données de près de 350 000 arbres étudiés dans plus de 12 000 placettes d’inventaire forestier. Chaque placette couvrait une superficie de 672 m2 et l’intensité d’échantillonnage était approximativement d’une placette par 2 400 ha. Deux indices ont été utilisés pour chacune des deux variables d’inventaire communément et précisément mesurées : le nombre d’espèces et l’indice de Shannon pour l’espèce d’arbre, et l’écart-type et l’indice de Shannon pour le diamètre des arbres. Quatre résultats importants peuvent être tirés de cette étude : (i) l’étendue de la corrélation spatiale des indices de diversité était faible, de l’ordre de 5 à 10 km, (ii) une proportion élevée de la diversité à l’échelle de la province a été calculée dans des surfaces circulaires dont le rayon est aussi petit que 15 km, (iii) la diversité en espèces et en diamètres avait une structure spatiale nettement définie du nord-ouest vers le sud-est et (iv) la diversité en diamètres α à l’échelle de la placette était fortement corrélée avec le diamètre moyen des arbres à l’échelle de la placette. [ABSTRACT FROM AUTHOR]

Examines the use of classical zero-shifting technique to synthesized the bandpass filters in direct coupled resonator forms. Utilization of circuit transformations; Transformation of direct coupled resonator filter circuits to cross-coupled forms; Application of quadruplet section to realize a complex transmission zeros quadruplet.

Abstract The biomass and biomass dynamics of forests are major uncertainties in our understanding of tropical environments. Remote sensing is often the only practical means of acquiring information on forest biomass but has not always been used successfully. Here the conventional approaches to the estimation of forest biomass from remotely sensed data were evaluated relative to techniques based on the application of artificial neural networks. Together these approaches were used to estimate and map the biomass of tropical forests in north-eastern Borneo from Landsat TM data. The neural networks were found to be particularly suited to the application. A basic multi-layer perceptron network, for example, provided estimates of biomass that were strongly correlated with those measured in the field (r = 0.80). Moreover, these estimates were more strongly correlated with biomass than those derived from 230 conventional vegetation indices, including the widely used normalized difference vegetation index (NDVI). [ABSTRACT FROM AUTHOR]