Tree diversity in a tropical agricultural-forest mosaic landscape in Honduras.

Biodiversity decline in the tropics requires the implementation of comprehensive landscape management where agricultural systems are necessarily an integral element of biodiversity conservation. This study evaluates the potential for taxonomic biodiversity conservation within an intensive livestock-agricultural-forest mosaic landscape in Catacamas, Honduras. Tree sampling was performed in 448 plots set up within different forest and agricultural land uses: secondary forests, agroforestry coffee plantations, agriculture, pastures, live fences and riparian forest. All trees with a minimum diameter at breast height of 10 cm were identified and measured. We characterized their tree structure and diversity, and compared tree diversity between the different uses. The results indicate a high degree of tree species diversity: 375 species identified, belonging to 74 families among the 15,096 trees inventoried across 84.2 hectares, including many rare species (40% of the species registered three individuals or fewer). Biodiversity indices for agroforestry coffee were found equivalent to those for natural secondary forests in the Catacamas landscape. Combining biodiversity conservation and agricultural production is possible in human-pressured tropical landscapes through tree cover maintenance. Enrichment practices combining local producers and technical knowledge may improve tree diversity in agricultural landscapes by prioritizing a mix of forest and introduced tree species (rare and with multiple uses).

Relationship between leaf functional traits and productivity in Aquilaria crassna (Thymelaeaceae) plantations: a tool to aid in the early selection of high-yielding trees.

Physiological traits are frequently used as indicators of tree productivity. Aquilaria species growing in a research planting were studied to investigate relationships between leaf-productivity traits and tree growth. Twenty-eight trees were selected to measure isotopic composition of carbon (δ13C) and nitrogen (δ15N) and monitor six leaf attributes. Trees were sampled randomly within each of four diametric classes (at 150 mm above ground level) ensuring the variability in growth of the whole population was represented. A model averaging technique based on the Akaike's information criterion was computed to identify whether leaf traits could assist in diameter prediction. Regression analysis was performed to test for relationships between carbon isotope values and diameter and leaf traits. Approximately one new leaf per week was produced by a shoot. The rate of leaf expansion was estimated as 1.45 mm day-1. The range of δ13C values in leaves of Aquilaria species was from -25.5‰ to -31‰, with an average of -28.4 ‰ (±1.5‰ SD). A moderate negative correlation (R2 = 0.357) between diameter and δ13C in leaf dry matter indicated that individuals with high intercellular CO2 concentrations (low δ13C) and associated low water-use efficiency sustained rapid growth. Analysis of the 95% confidence of best-ranked regression models indicated that the predictors that could best explain growth in Aquilaria species were δ13C, δ15N, petiole length, number of new leaves produced per week and specific leaf area. The model constructed with these variables explained 55% (R2 = 0.55) of the variability in stem diameter. This demonstrates that leaf traits can assist in the early selection of high-productivity trees in Aquilaria species.