A citizen centred urban network for weather and air quality in Australian schools.

High-quality, standardized urban canopy layer observations are a worldwide necessity for urban climate and air quality research and monitoring. The Schools Weather and Air Quality (SWAQ) network was developed and distributed across the Greater Sydney region with a view to establish a citizen-centred network for investigation of the intra-urban heterogeneity and inter-parameter dependency of all major urban climate and air quality metrics. The network comprises a matrix of eleven automatic weather stations, nested with a web of six automatic air quality stations, stretched across 2779 km2, with average spacing of 10.2 km. Six meteorological parameters and six air pollutants are recorded. The network has a focus on Sydney's western suburbs of rapid urbanization, but also extends to many eastern coastal sites where there are gaps in existing regulatory networks. Observations and metadata are available from September 2019 and undergo routine quality control, quality assurance and publication. Metadata, original datasets and quality-controlled datasets are open-source and available for extended academic and non-academic use.

Future changes in extreme weather and pyroconvection risk factors for Australian wildfires.

Extreme wildfires have recently caused disastrous impacts in Australia and other regions of the world, including events with strong convective processes in their plumes (i.e., strong pyroconvection). Dangerous wildfire events such as these could potentially be influenced by anthropogenic climate change, however, there are large knowledge gaps on how these events might change in the future. The McArthur Forest Fire Danger Index (FFDI) is used to represent near-surface weather conditions and the Continuous Haines index (CH) is used here to represent lower to mid-tropospheric vertical atmospheric stability and humidity measures relevant to dangerous wildfires and pyroconvective processes. Projected changes in extreme measures of CH and FFDI are examined using a multi-method approach, including an ensemble of global climate models together with two ensembles of regional climate models. The projections show a clear trend towards more dangerous near-surface fire weather conditions for Australia based on the FFDI, as well as increased pyroconvection risk factors for some regions of southern Australia based on the CH. These results have implications for fields such as disaster risk reduction, climate adaptation, ecology, policy and planning, noting that improved knowledge on how climate change can influence extreme wildfires can help reduce future impacts of these events.

Spatial variation in the climatic predictors of species compositional turnover and endemism.

Previous research focusing on broad-scale or geographically invariant species-environment dependencies suggest that temperature-related variables explain more of the variation in reptile distributions than precipitation. However, species-environment relationships may exhibit considerable spatial variation contingent upon the geographic nuances that vary between locations. Broad-scale, geographically invariant analyses may mask this local variation and their findings may not generalize to different locations at local scales. We assess how reptile-climatic relationships change with varying spatial scale, location, and direction. Since the spatial distributions of diversity and endemism hotspots differ for other species groups, we also assess whether reptile species turnover and endemism hotspots are influenced differently by climatic predictors. Using New Zealand reptiles as an example, the variation in species turnover, endemism and turnover in climatic variables was measured using directional moving window analyses, rotated through 360°. Correlations between the species turnover, endemism and climatic turnover results generated by each rotation of the moving window were analysed using multivariate generalized linear models applied at national, regional, and local scales. At national-scale, temperature turnover consistently exhibited the greatest influence on species turnover and endemism, but model predictive capacity was low (typically r (2) = 0.05, P < 0.001). At regional scales the relative influence of temperature and precipitation turnover varied between regions, although model predictive capacity was also generally low. Climatic turnover was considerably more predictive of species turnover and endemism at local scales (e.g., r (2) = 0.65, P < 0.001). While temperature turnover had the greatest effect in one locale (the northern North Island), there was substantial variation in the relative influence of temperature and precipitation predictors in the remaining four locales. Species turnover and endemism hotspots often occurred in different locations. Climatic predictors had a smaller influence on endemism. Our results caution against assuming that variability in temperature will always be most predictive of reptile biodiversity across different spatial scales, locations and directions. The influence of climatic turnover on the species turnover and endemism of other taxa may exhibit similar patterns of spatial variation. Such intricate variation might be discerned more readily if studies at broad scales are complemented by geographically variant, local-scale analyses.

Temporal Geobiotic Mapping: a conceptual mapping technique toward visualising geobiotic areas in cross-section

Geobiota are defined by taxic assemblages (i.e., biota) and their defining abiotic breaks, which are mapped in cross-section to reveal past and future biotic boundaries. We term this conceptual approach Temporal Geobiotic Mapping (TGM) and offer it as a conceptual approach for biogeography. TGM is based on geological cross-sectioning, which creates maps based on the distribution of biota and known abiotic factors that drive their distribution, such as climate, topography, soil chemistry and underlying geology. However, the availability of abiotic data is limited for many areas. Unlike other approaches, TGM can be used when there is minimal data available. In order to demonstrate TGM, we use the well-known area in the Blue Mountains, New South Wales (NSW), south-eastern Australia and show how surface processes such as weathering and erosion affect the future distribution of a Moist Basalt Forest taxic assemblage. Biotic areas are best represented visually as maps, which can show transgressions and regressions of biota and abiota over time. Using such maps, a biogeographer can directly compare animal and plant distributions with features in the abiotic environment and may identify significant geographical barriers or pathways that explain biotic distributions.

Quantifying high resolution transitional breaks in plant and mammal distributions at regional extent and their association with climate, topography and geology.

OBJECTIVES: We quantify spatial turnover in communities of 1939 plant and 59 mammal species at 2.5 km resolution across a topographically heterogeneous region in south-eastern Australia to identify distributional breaks and low turnover zones where multiple species distributions overlap. Environmental turnover is measured to determine how climate, topography and geology influence biotic turnover differently across a variety of biogeographic breaks and overlaps. We identify the genera driving turnover and confirm the versatility of this approach across spatial scales and locations. METHODS: Directional moving window analyses, rotated through 360°, were used to measure spatial turnover variation in different directions between gridded cells containing georeferenced plant and mammal occurrences and environmental variables. Generalised linear models were used to compare taxic turnover results with equivalent analyses for geology, regolith weathering, elevation, slope, solar radiation, annual precipitation and annual mean temperature, both uniformly across the entire study area and by stratifying it into zones of high and low turnover. Identified breaks and transitions were compared to a conservation bioregionalisation framework widely used in Australia. RESULTS/SIGNIFICANCE: Detailed delineations of plant and mammal turnover zones with gradational boundaries denoted subtle variation in species assemblages. Turnover patterns often diverged from bioregion boundaries, though plant turnover adhered most closely. A prominent break zone contained either comparable or greater numbers of unique genera than adjacent overlaps, but these were concentrated in a small subsection relatively under-protected by conservation reserves. The environmental correlates of biotic turnover varied for different turnover zones in different subsections of the study area. Topography and temperature showed much stronger relationships with plant turnover in a topographically complex overlap, relative to a lowland overlap where weathering was most predictive. This method can quantify transitional turnover patterns from small to broad extents, at different resolutions for any location, and complements broad-scale bioregionalisation schemes in conservation planning.