PHYTOSOCIOLOGY AND ECOLOGY OF THE NATURAL DRY-GRASS COMMUNITIES ON OAHU, HAWAII

Using the Braun-Blanquet and ordination techniques, nine dry-grass community types were recognized on Oahu,seven of which were dominated by exotic grasses and two by native grasses, Hctcrnpogna eontortus and Erarjrostis variabilis.These community types occured in summer-drought, summer-dry and humid climates.The distribution of certain community types could be correlated directly with rainfall and soil pH. In the summer-drought climate the occurrence of the community types was related to topography,wind exposure, rockiness of the land surface and stoniness of the soil.The nine community types were not related to the established soil series, organic matter content and watsr retaining' capacity of the surface soils.Three distinct soil-water regimes were recognized in five community types: drought, dry and wet types.Seasonal variations in soil-water content were correlated closely with the rainfall pattern.The introduction and spread of exotic species resulted in a gradual disappearance of the native grass communities in the summer-drought zone. In the summer-dry zone, Grevillea robiista. trees and Meliiiis minutiflora grass mats were invading the Rhynchelytrum repens community. Artdropogon virginiciis, introduced in 1932, formed a wide spread herbaceous community in the humid zone. In some places, this community was invaded by Dicranopteris linearis fern mats and trees of Acacia, koa or Metrosideros collina. Fire in both the summer-dry and humid zones maintained and extended the grass communities

The PABITRA Project: Island landscapes under global change

The Pacific-Asia Biodiversity Transect (PABITRA) is a network of the Ecosystem Division in the Pacific Science Association's Task Force on Biodiversity. The PABITRA project seeks to develop a network of ocean-to mountain transects on islands across the Pacific to test hypotheses about biodiversity and promote sustainable use of island ecosystems under the influence of global change. A specific objective of PABITRA was to establish an ocean to-mountain transect in Fiji with major involvement of the resident islanders. Along this transect, a number of biodiversity study sites were to be selected for further research. The transect was established during two consecutive field workshops, from 18 November to 3 December 2002. Involved were 25 University of the South Pacific (USP) students, eight local faculty including Fiji Government and nongovernmental organization officials, and seven overseas collaborators. The outcome was documented in a 69-page illustrated report issued by the USP Institute of Applied Sciences as well as at a special symposium presented during the 20th Pacific Science Congress in Bangkok (17-21 March 2003) titled "Island Landscapes under Global Change: the PABITRA Project." Seven papers presented by members of the Fijian PABITRA group are published here, following this introductory paper. In addition, five papers introducing PABITRA activities outside Fiji are included in this special issue. The PABITRA project is ongoing and it is hoped that these papers will stimulate broad interest and participation in PABITRA's key objectives of promoting integrative resource management in Pacific Island environments

ガラパゴスのスカレシア林の個体群構造、一斉枯死、再生について

The original publication is available at www.springerlink.co

Ohia rain forest study: ecological investigations of the ohia dieback problem in Hawaii

Reports were scanned in black and white at a resolution of 600 dots per inch and were converted to text using Adobe Paper Capture Plug-in.This final report summarizes the more important results of a two year study of the ohia (Metrosideros collina subsp. polymorpha) rain forest, extending from within Hawaii Volcanoes National Park north across the east flank of Mauna Kea, Island Hawaii. The study focus was on the ohia dieback which occurs in many areas of this terrain. A 1:48,000 vegetation map was produced, which is included in selected copies of this report. In addition, an independent habitat classification was developed from physical soil and moisture regime differences occurring in the area. Over 35 ohia forest stands were sampled in detail for their ohia population structures and 39 releves were analyzed for their floristic content. Five different forms of dieback were recognized. Two of these, called the Dryland and Wetland Diebacks appear to be the more rapid and dramatic forms. Their causes are not from disease or insect attack, but are presumed to be from climatic triggers, acting through the soil. These diebacks are clearly associated with ohia-stand rejuvenation. A third form of dieback, here called Bog-formation Dieback, appears to be a slower form of stand dieback related to permanent site changes. An Ohia-displacement Dieback occurs in the Olaa Tract area, where tree ferns seem to gradually take over the habitats. Here the dieback cause appears to be overmaturity. Individual tree dieback, the fifth form of dieback, is found as an isolated, but common phenomenon in many non-dieback stands examined. All diebacks appear to have natural causes, which are suggested in detail. A new theory is presented, which proposes that there are a number of dynamic phases, including the dieback, which provide for the perpetuation of the shade-intolerant, dominant tree species (ohia) in this rainforest ecosystem.National Park Service Contract No. CX 8000 6 000

Using Plant Functional Attributes to Quantify Site Productivity and Growth Patterns in Mixed Forests

Forest growth models are one of several important prerequisites for sustainable management. The complexity of tropical moist forest means that there is often little objective information to classify sites and species for growth modelling and yield prediction. Classification based on observable morphological characteristics may be a useful surrogate for, or supplement to other alternatives. This study investigated the utility of plant functional attributes (PFAs) for site and species classification. PFAs describe a plant in terms of its photosynthetic and vascular support system, and the sum of individual PFAs for all species on a plot provides an efficient summary of vegetation features at the site. Preliminary observations suggested that the PFA summary may also indicate site productivity, and that specific PFAs may be used to group species for modelling growth and yield. Data from 17 permanent plots in the tropical rainforests of North Queensland were used to test these preliminary observations. Standard PFA proformas were completed for each plot in January 1995, and the relationships between the PFAs, site productivity and specific growth patterns were examined using discriminant analysis, linear regression and standard statistical tests. Results indicate that mean leaf size, and the incidence of species with vertical leaf inclination (>30° above horizontal) are significantly correlated with site productivity. Of the PFAs assessed, five elements appear to offer a useful basis for grouping species for modelling: leaf size and inclination, a furcation index (i.e., relative height to first fork or break in the main stem), and the presence of lenticels and chlorophyllous tissue on the main stem. The restricted nature of our database limits comment on the general utility of the method, but results suggest that further work on PFAs is warranted

Bayesian classification of vegetation types with Gaussian mixture density fitting to indicator values.

Question: Is it possible to mathematically classify relevés into vegetation types on the basis of their average indicator values, including the uncertainty of the classification? Location: The Netherlands. Method: A large relevé database was used to develop a method for predicting vegetation types based on indicator values. First, each relevé was classified into a phytosociological association on the basis of its species composition. Additionally, mean indicator values for moisture, nutrients and acidity were computed for each relevé. Thus, the position of each classified relevé was obtained in a three-dimensional space of indicator values. Fitting the data to so called Gaussian Mixture Models yielded densities of associations as a function of indicator values. Finally, these density functions were used to predict the Bayesian occurrence probabilities of associations for known indicator values. Validation of predictions was performed by using a randomly chosen half of the database for the calibration of densities and the other half for the validation of predicted associations. Results and Conclusions: With indicator values, most relevés were classified correctly into vegetation types at the association level. This was shown using confusion matrices that relate (1) the number of relevés classified into associations based on species composition to (2) those based on indicator values. Misclassified relevés belonged to ecologically similar associations. The method seems very suitable for predictive vegetation models