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Rapid characterisation of vegetation structure to predict refugia and climate change impacts across a global biodiversity hotspot

Identification of refugia is an increasingly important adaptation strategy in conservation planning under rapid anthropogenic climate change. Granite outcrops (GOs) provide extraordinary diversity, including a wide range of taxa, vegetation types and habitats in the Southwest Australian Floristic Region (SWAFR). However, poor characterization of GOs limits the capacity of conservation planning for refugia under climate change. A novel means for the rapid identification of potential refugia is presented, based on the assessment of local-scale environment and vegetation structure in a wider region. This approach was tested on GOs across the SWAFR. Airborne discrete return Light Detection And Ranging (LiDAR) data and Red Green and Blue (RGB) imagery were acquired. Vertical vegetation profiles were used to derive 54 structural classes. Structural vegetation types were described in three areas for supervised classification of a further 13 GOs across the region.Habitat descriptions based on 494 vegetation plots on and around these GOs were used to quantify relationships between environmental variables, ground cover and canopy height. The vegetation surrounding GOs is strongly related to structural vegetation types (Kappa = 0.8) and to its spatial context. Water gaining sites around GOs are characterized by taller and denser vegetation in all areas. The strong relationship between rainfall, soil-depth, and vegetation structure (R2 of 0.8–0.9) allowed comparisons of vegetation structure between current and future climate. Significant shifts in vegetation structural types were predicted and mapped for future climates. Water gaining areas below granite outcrops were identified as important putative refugia. A reduction in rainfall may be offset by the occurrence of deeper soil elsewhere on the outcrop. However, climate change interactions with fire and water table declines may render our conclusions conservative. The LiDAR-based mapping approach presented enables the integration of site-based biotic assessment with structural vegetation types for the rapid delineation and prioritization of key refugia

Discriminatory ability of right atrial volumes with two- and three-dimensional echocardiography to detect elevated right atrial pressure in pulmonary hypertension

Aims: Pulmonary hypertension (PH) patients have high mortality due to right ventricular failure. Predictors of poor prognostic outcome are increased right atrial volume (RAV) and elevated mean right atrial pressure (mRAP). Our aim was to determine whether RAV measured with 2D echocardiography (2DE) and 3D echocardiography (3DE) can detect elevated mRAP in patients evaluated for PH. Methods: Of 85 patients prospectively evaluated for PH, 44 patients (63 ± 15 years, 57% female) had 2DE, 3DE and right heart catheterization within 48 h and were in sinus rhythm. Maximum (RAVmax) and minimum (RAVmin) volumes were measured with 3DE. 2D maximum RAV and RA area, inferior vena cava diameter and collapsibility were measured. Invasive mRAP > 8 mmHg was predefined as elevated. Results: RAVmax and RAVmin correlated with mRAP (r = 0·40 and r = 0·35, P8 mmHg. The optimal threshold was 57 ml m-2 for RAVmax, 31 ml m-2 for RAVmin and 36 ml m-2 for 2DE RAV. Conclusions: Enlarged RA measures with 2DE and 3DE have better discriminatory ability compared with IVC measures, to detect elevated mRAP in patients evaluated for PH