Predicting forest attributes In southeast Alaska using artificial neural networks

Artificial neural network (ANN) methods are used to predict forest characteristics. The data source is the Southeast Alaska (SEAK) Grid Inventory, a ground survey compiled by the USDA Forest Service at several thousand sites. The main objective of this article is to predict characteristics at unsurveyed locations between grid sites. A secondary objective is to evaluate the relative performance of different ANNs. Data from the grid sites are used to train six ANNs: multilayer perceptron, fuzzy ARTMAP, probabilistic, generalized regression, radial basis function, and learning vector quantization. A classification and regression tree method is used for comparison. Topographic variables are used to construct models: latitude and longitude coordinates, elevation, slope, and aspect. The models classify three forest characteristics: crown closure, species land cover, and tree size/structure. Models are constructed using n-fold cross-validation. Predictive accuracy is calculated using a method that accounts for the influence of misclassification as well as measuring correct classifications. The probabilistic and generalized regression networks are found to be the most accurate. The predictions of the ANN models are compared with a classification of the Tongass national forest in southeast Alaska based on the interpretation of satellite imagery and are found to be of similar accuracy.

Enchytraeid worms retard polycyclic aromatic hydrocarbon degradation in a coniferous forest soil

In this study the fate of naphthalene, fluorene and pyrene were investigated in the presence and absence of enchytraeid worms. Microcosms were used, which enabled the full fate of ¹⁴C-labelled PAHs to be followed. Between 60 and 70% of naphthalene was either mineralised or volatilised, whereas over 90% of the fluorene and pyrene was retained within the soil. Mineralisation and volatilisation of naphthalene was lower in the presence of enchytraeid worms. The hypothesis that microbial mineralisation of naphthalene was limited by enchytraeids because they reduce nutrient availability, and hence limit microbial carbon turnover in these nutrient poor soils, was tested. Ammonia concentrations increased and phosphorus concentrations decreased in all microcosms over the 56 d experimental period. The soil nutrient chemistry was only altered slightly by enchytraeid worms, and did not appear to be the cause of retardation of naphthalene mineralisation. The results suggest that microbial availability and volatilisation of naphthalene is altered as it passes through enchytraeid worms due to organic material encapsulation. © 2004 Elsevier Ltd. All rights reserved.

Degradation of the polycyclic aromatic hydrocarbon (PAH) fluorene is retarded in a Scots pine ectomycorrhizosphere

Polycyclic aromatic hydrocarbons (PAHs) are an important class of persistent organic pollutants (POPs) in the environment and accumulate in forest soils. These soils are often dominated by ectomycorrhizal (EcM) roots, but little is known about how EcM fungi degrade PAHs, or the overall effect of field colonized EcM roots on the fate of PAHs. The ability of eight EcM fungi to degrade PAHs in liquid culture spiked with ¹⁴C labelled PAHs was investigated. Microcosms were used to determine the impact of naturally colonized mycorrhizal pine seedlings on PAH mineralization and volatilization. Only two EcM fungi (Thelephora terrestris and Laccaria laccata) degraded at least one PAH and none were able to mineralize the PAHs in pure culture. Where degradation occurred, the compounds were only mono-oxygenated. EcM pine seedlings did not alter naphthalene mineralization or volatilization but retarded fluorene mineralization by 35% compared with unplanted, ectomycorrhizosphere soil inoculated, microcosms. The EcM fungi possessed limited PAH degrading abilities, which may explain why EcM dominated microcosms retarded fluorene mineralization. This observation is considered in relation to the 'Gadgil-effect', where retarded litter decomposition has been observed in the presence of EcM roots. © New Phytologist (2004).