E. Westinga

The intrasponge fauna of Spheciospongia vesparia (Porifera, Demospongiae) at Curaçao and bonaire

The infauna of 35 individuals of Spheciospongia vesparia (Lamarck, 1814) of different volumes and from different sites and depths have been inventoried and compared. The number of sponge-inhabiting taxa is logarithmically related to sponge volume. Biomass and total number of the animals contained in the sponge are directly proportional to sponge volume. Numerical and taxonomic composition of infaunas from different sampling sites is fairly constant. Biomass and total number of sponge-inhabiting animals is not significantly different for any of the 4 sampling sites. Several taxa, however, are more abundant in sponges from one or more localities. The ratio of total biomass to total number of intrasponge fauna is found to be significantly smaller for sponges collected in deep water than in shallow water. Differences from and similarities with Pearses results (1932, 1950) on the infauna of the same sponge species at Dry Tortugas and Bimini are discussed. The relation of the number of contained taxa and the volume of a sponge is compared with the relation of island size and number of taxa present according to MacArthur and Wilsons island-theory (MacArthur, 1972). Finally the erratic occurrence of some taxa as opposed to the highly regular occurrence of some other taxa is discussed. It is concluded that the composition of the sponge-infauna in specimens larger than 11 is highly constant and that the sponge-inhabiting fauna constitutes an ecological community.

Fine resolution distribution modelling of endemics in Majella National Park, Central Italy

Abstract Majella National Park in central Italy is known to be an endemic-rich area, but distributions of its endemics have not been comprehensively studied. Endemics with 10 or more records and spatial uncertainties at <5 km were extracted from the Central-Apennine floristic geodatabase and the MNP Seed Index. Nine environmental predictor layers were prepared at 90 and 30 m resolution. A stepwise Maximum Entropy (Maxent) model was generated per endemic to achieve the most parsimonious result at an area under the curve > 0.8. Arctic-alpine elevation, edaphic barrens and low open-vegetation, individually or in pairs, were found to be predictive for endemics. Forty-eight endemics, 10 of which exclusive, were recorded and Maxent-predicted for the Majella massif. Subsets of 38 endemics were recorded on other mountains in proportion to their arctic-alpine area, thus conforming to the Island Theory. Maxent confirmed its strengths also at fine resolutions and, in addition, showed to be robust across predictor layers at both resolutions. A linear species-area relationship appeared superior to the Maxent model in predicting the number of endemics per arctic-alpine “island”. Our findings suggest the need for a proactive management of the botanical biodiversity contained in the alpine and montane barrens and low-open vegetation.

Assessment of degraded mattoral land using remote sensing imagery in Guadalteba Area, Spain

Natural land cover information is important for analysing and understanding of the current terrestrial situation, especially in the study area that is facing the environmental deteriorating increasingly. The study combined the remote sensing Aster data and ground truth to improve 2001 land cover map of Guadalteba area in Spain, and increased the accuracy from 47% to 70%. The general land cover map produced about the Guadalteba study area outlines the distribution of the vegetation type and the current natural land cover in the area. Based on this improved general land cover map, the natural cover map gave an indication of the present location of nature and agriculture areas. The shrub land degradation map identified location of various shrub/matorral areas and different levels of degradation. The further analysis and discussion were done. The output maps indicated that much of the natural cover mostly dominated by formations of shrubs has been changed to agriculture and other land uses. It is observed that shrubland covers a small percentage, approximately 9% of the study area, due to land degradation in most parts caused by human interfere.

FAME: a forest assessment and monitoring environment scenario

Effective management of forest resources requires suitable, up-to-date information on the state, extent and distribution of forest. Remote sensing data can provide this information. To enable the use of remote sensing data for global forest monitoring, provisions are required to allow operational processing of the data to standardized products. A scenario for the development of a Forest Assessment and Monitoring Environment is presented. Firstly, a pilot RESPAS (REmote Sensing Preprocessing and Archiving Systems) is developed, a suitable tool for forest management, to compile information on global forests. Secondly, RESPAS is upgraded to improve its functionality and to introduce FMS (Forestry Management System). Thirdly, RESPAS is extended by introducing remote sensing data from newly launched sensors. By introducing this three-step approach, standardized remote sensing products will become available for use in sustainable forest management giving information on the state, extent and distribution of tropical forests.<<ETX>>