Impacts of a fuel oil spill on seagrass meadows in a subtropical port, Gladstone, Australia - The value of long-term marine habitat monitoring in high risk areas.

We used an established seagrass monitoring programme to examine the short and longer-term impacts of an oil spill event on intertidal seagrass meadows. Results for potentially impacted seagrass areas were compared with existing monitoring data and with control seagrass meadows located outside of the oil spill area. Seagrass meadows were not significantly affected by the oil spill. Declines in seagrass biomass and area 1 month post-spill were consistent between control and impact meadows. Eight months post-spill, seagrass density and area increased to be within historical ranges. The declines in seagrass meadows were likely attributable to natural seasonal variation and a combination of climatic and anthropogenic impacts. The lack of impact from the oil spill was due to several mitigating factors rather than a lack of toxic effects to seagrasses. The study demonstrates the value of long-term monitoring of critical habitats in high risk areas to effectively assess impacts.

Springbrook : Challenges in developing a long-term, rainforest wireless sensor network

We describe the design, development and learnings from the first phase of a rainforest ecological sensor network at Springbrook - part of a World Heritage precinct in South East Queensland. This first phase is part of a major initiative to develop the capability to provide reliable, long-term monitoring of rainforest ecosystems. We focus in particular on our analysis around energy and communication challenges which need to be solved to allow for reliable, long-term deployments in these types of environments.

Sampling the soil in long-term forest plots: The implications of spatial variation

Long-term monitoring of forest soils as part of a pan-European network to detect environmental change depends on an accurate determination of the mean of the soil properties at each monitoring event. Forest soil is known to be very variable spatially, however. A study was undertaken to explore and quantify this variability at three forest monitoring plots in Britain. Detailed soil sampling was carried out, and the data from the chemical analyses were analysed by classical statistics and geostatistics. An analysis of variance showed that there were no consistent effects from the sample sites in relation to the position of the trees. The variogram analysis showed that there was spatial dependence at each site for several variables and some varied in an apparently periodic way. An optimal sampling analysis based on the multivariate variogram for each site suggested that a bulked sample from 36 cores would reduce error to an acceptable level. Future sampling should be designed so that it neither targets nor avoids trees and disturbed ground. This can be achieved best by using a stratified random sampling design.

MARECHIARA-mesozooplankton long-term time-series at the fixed coastal station in the Gulf of Naples: abundance and biomass, data for the years 1984-2006

The MARECHIARA-mesozooplankton dataset contains mesozooplankton data collected in the ongoing time-series at Sation MC (40°48.5' N, 14°15' E) in the Gulf of Naples. This dataset spans over the period 1984-2006 and contains data of mesozooplankton abundance and species composition as well as biomass (as dry weight). Mesozooplankton was regularly sampled in 1984-1990 and 1995-2006, only a few samples were collected in 1991-1992 and no samples in 1993-1994. During the first period of the series sampling frequency was fortnightly, and weekly since 1995.