Characterising and Predicting Benthic Biodiversity for Conservation Planning in Deepwater Environments

Understanding patterns of biodiversity in deep sea systems is increasingly important because human activities are extending further into these areas. However, obtaining data is difficult, limiting the ability of science to inform management decisions. We have used three different methods of quantifying biodiversity to describe patterns of biodiversity in an area that includes two marine reserves in deep water off southern Australia. We used biological data collected during a recent survey, combined with extensive physical data to model, predict and map three different attributes of biodiversity: distributions of common species, beta diversity and rank abundance distributions (RAD). The distribution of each of eight common species was unique, although all the species respond to a depth-correlated physical gradient. Changes in composition (beta diversity) were large, even between sites with very similar environmental conditions. Composition at any one site was highly uncertain, and the suite of species changed dramatically both across and down slope. In contrast, the distributions of the RAD components of biodiversity (community abundance, richness, and evenness) were relatively smooth across the study area, suggesting that assemblage structure (i.e. the distribution of abundances of species) is limited, irrespective of species composition. Seamounts had similar biodiversity based on metrics of species presence, beta diversity, total abundance, richness and evenness to the adjacent continental slope in the same depth ranges. These analyses suggest that conservation objectives need to clearly identify which aspects of biodiversity are valued, and employ an appropriate suite of methods to address these aspects, to ensure that conservation goals are met

Dopamine transporter (DAT1) and dopamine receptor D4 (DRD4) genotypes differentially impact on electrophysiological correlates of error processing

Peer reviewedPublisher PD

Efficacy and Safety of Inhaled Carbon Monoxide during Pulmonary Inflammation in Mice

Background: Pulmonary inflammation is a major contributor to morbidity in a variety of respiratory disorders, but treatment options are limited. Here we investigate the efficacy, safety and mechanism of action of low dose inhaled carbon monoxide (CO) using a mouse model of lipopolysaccharide (LPS)-induced pulmonary inflammation. Methodology: Mice were exposed to 0–500 ppm inhaled CO for periods of up to 24 hours prior to and following intratracheal instillation of 10 ng LPS. Animals were sacrificed and assessed for intraalveolar neutrophil influx and cytokine levels, flow cytometric determination of neutrophil number and activation in blood, lung and lavage fluid samples, or neutrophil mobilisation from bone marrow. Principal Findings: When administered for 24 hours both before and after LPS, inhaled CO of 100 ppm or more reduced intraalveolar neutrophil infiltration by 40–50%, although doses above 100 ppm were associated with either high carboxyhemoglobin, weight loss or reduced physical activity. This anti-inflammatory effect of CO did not require pre-exposure before induction of injury. 100 ppm CO exposure attenuated neutrophil sequestration within the pulmonary vasculature as well as LPS-induced neutrophilia at 6 hours after LPS, likely due to abrogation of neutrophil mobilisation from bone marrow. In contrast to such apparently beneficial effects, 100 ppm inhaled CO induced an increase in pulmonary barrier permeability as determined by lavage fluid protein content and translocation of labelled albumin from blood to the alveolar space