2003 Habitat Maps derived from Grey Nurse Shark (GNS) Project of Wolf Rock, Double Island Point, Queensland, Australia

Surveying habitats critical to the survival of grey nurse sharks in South-East Queensland has mapped critical habitats, gathered species inventories and developed protocols for ecological monitoring of critical habitats in southern Queensland. This information has assisted stakeholders with habitat definition and effective management. In 2002 members of UniDive applied successfully for World Wide Fund for Nature, Threatened Species Network funds to map the critical Grey Nurse Shark Habitats in south east Queensland. UniDive members used the funding to survey, from the boats of local dive operators, Wolf Rock at Double Island Point, Gotham, Cherub's Cave, Henderson's Rock and China Wall at North Moreton and Flat Rock at Point Look Out during 2002 and 2003. These sites are situated along the south east Queensland coast and are known to be key Grey Nurse Shark aggregation sites. During the project UniDive members were trained in mapping and survey techniques that include identification of fish, invertebrates and substrate types. Training was conducted by experts from the University of Queensland (Centre of Marine Studies, Biophysical Remote Sensing) and the Queensland Parks and Wildlife Service who are also UniDive members. The monitoring methods (see methods) are based upon results of the UniDive Coastcare project from 2002, the international established Reef Check program and research conducted by Biophysical Remote Sensing and the Centre of Marine Studies. Habitats were mapped using a combination of towed GPS photo transects, aerial photography, bathymetry surveys and expert knowledge. This data provides georeferenced information regarding the major features of each of Sites mapped including Wolf Rock

Benthic cyanobacterial mat (BCM) abundance on samples from the coast of Curacao

Benthic cyanobacterial mats (BCMs) are impacting coral reefs worldwide. However, the factors and mechanisms driving their proliferation are unclear. We conducted a multi-year survey around the Caribbean island of Curaçao, which revealed highest BCM abundance on sheltered reefs close to urbanised areas. Reefs with high BCM abundance were also characterised by high benthic cover of macroalgae and low cover of corals. Nutrient concentrations in the water-column were consistently low, but markedly increased just above substrata (both sandy and hard) covered with BCMs. This was true for sites with both high and low BCM coverage, suggesting that BCM growth is stimulated by a localised, substrate-linked release of nutrients from the microbial degradation of organic matter. This hypothesis was supported by a higher organic content in sediments on reefs with high BCM coverage, and by an in situ experiment which showed that BCMs grew within days on sediments enriched with organic matter (Spirulina). We propose that nutrient runoff from urbanised areas stimulates phototrophic blooms and enhances organic matter concentrations on the reef. This organic matter is transported by currents and settles on the seabed at sites with low hydrodynamics. Subsequently, nutrients released from the organic matter degradation fuel the growth of BCMs. Improved management of nutrients generated on land should lower organic loading of sediments and other benthos (e.g. turf and macroalgae) to reduce BCM proliferation on coral reefs.

Position measurements at five permanent GPS stations in the Bavarian Alps as part of the Geodetic Alpine Integrated Network (GAIN) of the ALPS-GPSQUAKENET project

In the frame of the transnational ALPS-GPSQUAKENET project, a component of the Alpine Space Programme of the European Community Initiative Programme (CIP) INTERREG III B, the Deutsches Geodätisches Forschungsinstitut (DGFI) in Munich, Germany, installed in 2005 five continuously operating permanent GPS stations located along the northern Alps boundary in Bavaria. The main objective of the ALPS-GPSQUAKENET project was to build-up a high-performance transnational space geodetic network of Global Positioning System (GPS) receivers in the Alpine region (the so-called Geodetic Alpine Integrated Network, GAIN). Data from this network allows for studying crustal deformations in near real-time to monitor Earthquake hazard and improve natural disaster prevention. The five GPS stations operatied by DGFI are mounted on concrete pillars attached to solid rock. The names of the stations are (from west to east) Hochgrat (HGRA), Breitenberg (BREI), Fahrenberg (FAHR), Hochries (HRIE) and Wartsteinkopf (WART). The provided data series start from October 7, 2005. Data are stored with a temporal spacing of 15 seconds in daily RINEX files.

Ecological classification of Herschel Island based on supervised classification of multispectral satellite imagery

Permafrost landscapes experience different disturbances and store large amounts of organic matter, which may become a source of greenhouse gases upon permafrost degradation. We analysed the influence of terrain and geomorphic disturbances (e.g. soil creep, active-layer detachment, gullying, thaw slumping, accumulation of fluvial deposits) on soil organic carbon (SOC) and total nitrogen (TN) storage using 11 permafrost cores from Herschel Island, western Canadian Arctic. Our results indicate a strong correlation between SOC storage and the topographic wetness index. Undisturbed sites stored the majority of SOC and TN in the upper 70 cm of soil. Sites characterised by mass wasting showed significant SOC depletion and soil compaction, whereas sites characterised by the accumulation of peat and fluvial deposits store SOC and TN along the whole core. We upscaled SOC and TN to estimate total stocks using the ecological units determined from vegetation composition, slope angle and the geomorphic disturbance regime. The ecological units were delineated with a supervised classification based on RapidEye multispectral satellite imagery and slope angle. Mean SOC and TN storage for the uppermost 1?m of soil on Herschel Island are 34.8 kg C/m**2 and 3.4 kg N/m**2, respectively.