Reproduction and Dispersal of Biological Soil Crust Organisms

Biological soil crusts (BSCs) consist of a diverse and highly integrated community of organisms that effectively colonize and collectively stabilize soil surfaces. BSCs vary in terms of soil chemistry and texture as well as the environmental parameters that combine to support unique combinations of organisms—including cyanobacteria dominated, lichen-dominated, and bryophyte-dominated crusts. The list of organismal groups that make up BSC communities in various and unique combinations include—free living, lichenized, and mycorrhizal fungi, chemoheterotrophic bacteria, cyanobacteria, diazotrophic bacteria and archaea, eukaryotic algae, and bryophytes. The various BSC organismal groups demonstrate several common characteristics including—desiccation and extreme temperature tolerance, production of various soil binding chemistries, a near exclusive dependency on asexual reproduction, a pattern of aerial dispersal over impressive distances, and a universal vulnerability to a wide range of human-related perturbations. With this publication, we provide literature-based insights as to how each organismal group contributes to the formation and maintenance of the structural and functional attributes of BSCs, how they reproduce, and how they are dispersed. We also emphasize the importance of effective application of molecular and microenvironment sampling and assessment tools in order to provide cogent and essential answers that will allow scientists and land managers to better understand and manage the biodiversity and functional relationships of soil crust communities

Novel Approach Identifies SNPs in SLC2A10 and KCNK9 with Evidence for Parent-of-Origin Effect on Body Mass Index

Marja-Liisa Lokki työryhmien Generation Scotland Consortium, LifeLines Cohort Study ja GIANT Consortium jäsenPeer reviewe

Spatial and temporal water quality changes during a large scale dredging operation

Dredging poses an environmental risk by increasing suspended sediment which has a range of effects on sensitive benthic communities, particularly coral reefs. Understanding spatial and temporal sediment related dredging impacts is essential to improve environmental impact assessment (EIA), monitoring and management of dredge operations. Despite the scale of global dredging projects, our understanding of the impacts is limited due to a lack of sufficiently large water quality datasets, the site specific nature of water quality changes during dredging, and the complex response of corals to the various associated suspended sediment pressures (i.e. reduced light, increased sediment deposition). Of particular importance during the EIA phase, and while monitoring dredging impacts, is understanding the distance to dredge effects i.e. how far the dredge related sediment impacts extend to more accurately predict environmental impacts and provide greater protection to coral reefs during dredging operations. The distance to dredge effects on water quality conditions (i.e. the spatial impacts of dredging) was investigated at Barrow Island, Western Australia, to determine how dredging affects turbidity, submarine light and sediment deposition conditions. Analysis was made possible using the largest water quality dataset ever collected prior to and during a large scale dredging operation. Water quality conditions prior to and during 18 months of dredging at Barrow Island, Western Australia, as well as the distance to dredge effects, were analysed to determine the impacts of dredging on turbidity, submarine light and sediment deposition. A high proportion of water quality sites (10/29) were located within 1.5 km south of dredging, allowing a high resolution of spatial dredging impact analysis close to the dredge zone. During dredging, water quality impacts were primarily confined to sites within 2 – 5 km south of the dredge zone, gradually decreasing to ambient levels at sites north of the dredge zone and sites > 10 km south. Turbidity maximums, means and standard deviations were up to 4 – 6 x higher, median light attenuation coefficients 1.5 x higher, median deposition levels up to 7 x higher and median overburden (dredge related turbidity, calculated using a simple statistical turbidity model which estimates natural turbidity during dredging) were 3 – 4 x higher at sites within 2 – 5 km south of dredging. Sites north of the dredge zone (extending up to 30 km north), sites > 10 km south of the dredge zone (extending up to 30 km south), and 2 dredge disposal perimeter sites were unaffected by dredging. There was also a strong relationship between light attenuation and turbidity at almost all of the 25 Barrow Island sites used to study light levels; 24 of the 25 sites had R² > 0.5 and 17 had R² ≥ 0.50. Turbidity conditions at Barrow Island were also characterised by using a range of different temporal analysis, including running mean and spectral analysis. By applying running means using increasing window sizes (from 1 hour to 30 days) separately to the baseline and dredge periods, it was revealed that dredging increases both the intensity and the duration of turbidity, with monthly, daily and hourly turbidity conditions higher at sites within 2 km of dredging; monthly averages were up to 25 NTU (compared to ~ 10 NTU at reference sites), daily averages up to 200 NTU (compared to maximum ~ 30 NTU at reference sites) and hourly averages up to 400 NTU (compared to maximum 100 NTU at reference sites). Spectral analysis also revealed the occurrence of horizontal advection during dredging at sites within 2 km of dredging. The use of a simple, statistical turbidity model to estimate natural turbidity (due to the natural resuspension processes of waves and tides) during dredging, and as a possible turbidity and deposition threshold exceedance monitoring tool, was investigated. The model is designed to be simple – an alternative method to the more complex three dimensional hydrodynamic models which require numerous inputs – and as such has expected limitations. Despite these limitations, the purpose of the model in this study is to decouple the natural turbidity and dredge induced turbidity, and possibly as an exceedance threshold tool. Model performance was tested in 2 different hydrodynamic settings – a clear water environment (Barrow Island) during a dredge operation and a turbid, energetic environment (Hay Point, Queensland) during a baseline water quality monitoring study. The model was successful at estimating daily turbidity at a few of the Hay Point and Barrow Island sites, with R² > 0.5 between modelled and measured turbidity at 83% of sites during the model test phase at Hay Point (although model skill scores were > 0.5 at only 1 site during the test phase), but only 38 % of sites had R² > 0.5 at Barrow Island and , but improvements could be made to both the input data and possibly more sophisticated parameter estimation tools (such as Bayesian analysis). The impact of dredging on submarine light levels was also investigated. Light attenuation coefficients (k) were analysed in lieu of measured PAR values due to non-uniform sensor depths across the water quality sites (depths ranged from ~ 4 to 14 m), which introduces a depth dependence to the distance to dredge analysis. Median light attenuation coefficients at sites closest to the main dredge zone (within 2 – 5 km) were between 0.4 – 0.55 m⁻¹ compared to all other sites which had levels 0.35 – 0.4 m⁻¹. As well as calculating k (using the Beer-Lambert Law) for the spatial analysis, the strong relationship between midday turbidity and k (R² > 0.5 at 96 % of sites and ≥ 0.7 at 68 %) was used to derive regression models of light attenuation from measured (midday) turbidity. The use of a double exponential method, which is an extension of the Beer Lambert Law developed by Paulson and Simpson (1977), was also investigated for estimating the light attenuation coefficients but was unsuitable for the Barrow Island study sites

Spatial patterns in water quality changes during dredging in tropical environments

Dredging poses a potential risk to tropical ecosystems, especially in turbidity-sensitive environments such as coral reefs, filter feeding communities and seagrasses. There is little detailed observational time-series data on the spatial effects of dredging on turbidity and light and defining likely footprints is a fundamental task for impact prediction, the EIA process, and for designing monitoring projects when dredging is underway. It is also important for public perception of risks associated with dredging. Using an extensive collection of in situ water quality data (73 sites) from three recent large scale capital dredging programs in Australia, and which included extensive pre-dredging baseline data, we describe relationships with distance from dredging for a range of water quality metrics. Using a criterion to define a zone of potential impact of where the water quality value exceeds the 80th percentile of the baseline value for turbidity-based metrics or the 20th percentile for the light based metrics, effects were observed predominantly up to three km from dredging, but in one instance up to nearly 20 km. This upper (~20 km) limit was unusual and caused by a local oceanographic feature of consistent unidirectional flow during the project. Water quality loggers were located along the principal axis of this flow (from 200 m to 30 km) and provided the opportunity to develop a matrix of exposure based on running means calculated across multiple time periods (from hours to one month) and distance from the dredging, and summarized across a broad range of percentile values. This information can be used to more formally develop water quality thresholds for benthic organisms, such as corals, filter-feeders (e.g. sponges) and seagrasses in future laboratory- and field-based studies using environmentally realistic and relevant exposure scenarios, that may be used to further refine distance based analyses of impact, potentially further reducing the size of the dredging footprint

Temporal patterns in seawater quality from dredging in tropical environments

Maintenance and capital dredging represents a potential risk to tropical environments, especially in turbidity-sensitive environments such as coral reefs. There is little detailed, published observational time-series data that quantifies how dredging affects seawater quality conditions temporally and spatially. This information is needed to test realistic exposure scenarios to better understand the seawater-quality implications of dredging and ultimately to better predict and manage impacts of future projects. Using data from three recent major capital dredging programs in North Western Australia, the extent and duration of natural (baseline) and dredging-related turbidity events are described over periods ranging from hours to weeks. Very close to dredging i.e. <500 m distance, a characteristic features of these particular case studies was high temporal variability. Over several hours suspended sediment concentrations (SSCs) can range from 100–500 mg L-1. Less turbid conditions (10–80 mg L-1) can persist over several days but over longer periods (weeks to months) averages were <10 mg L-1. During turbidity events all benthic light was sometimes extinguished, even in the shallow reefal environment, however a much more common feature was very low light ‘caliginous’ or daytime twilight periods. Compared to pre-dredging conditions, dredging increased the intensity, duration and frequency of the turbidity events by 10-, 5- and 3-fold respectively (at sites <500 m from dredging). However, when averaged across the entire dredging period of 80–180 weeks, turbidity values only increased by 2–3 fold above pre-dredging levels. Similarly, the upper percentile values (e.g., P99, P95) of seawater quality parameters can be highly elevated over short periods, but converge to values only marginally above baseline states over longer periods. Dredging in these studies altered the overall probability density distribution, increasing the frequency of extreme values. As such, attempts to understand the potential biological impacts must consider impacts across telescoping-time frames and changes to extreme conditions in addition to comparing central tendency (mean/median). An analysis technique to capture the entire range of likely conditions ove

Distance decay relationships based on light for the Barrow Island dredging program.

<p>Shown are distance relationships based on the 20^th percentile of the daily light integral (DLI) value for 1 day (A), 1 week (B) and 2 week running means (C); and the total number of days in near-darkness (normalised to 1 year) for DLI threshold values of ~0 mol m^-2 photons (D), 0.5 mol m^-2 photons (E) and 2.0 mol m^-2 photons (F).</p

(A) Total photosynthetically active radiation (PAR) daily light integral (DLI, mol photons m^-2) percentile values for running means calculated on time scales of 1, 14 and 30 days for all sites for the Barrow Island project. (B) Mean, median, 80^th percentile and maximum number of consecutive days in darkness and semi-darkness and (C) and mean fortnightly numbers of days for 4 different semi-darkness cut-off thresholds at all sites for the Barrow Island dredging project (1, 5, 10 and 20 μmol photons m^-2 s^-1; equivalent to DLI values of 0.04, 0.2, 0.4, and 0.8 mol photons m^-2 d^-1).

<p>White symbols represent percentiles for the baseline period (pre-dredging period), grey symbols represent reference sites during the dredging period and black symbols represent sites close to (<2 km) the dredging.</p

Intensity, duration and frequency (IDF) analysis of the seawater quality data at selected dredge-influenced site (Dredg.) and reference site (Ref.) for the Barrow Island, Cape Lambert and Burrup Peninsula dredging programs.

<p>The analysis was carried out separately at daily and hourly temporal scale. Intensity values represent the 95% percentile of turbidity for the site for each period. Duration values represent the 95^th percentile of the duration (days) of exceedance events (where exceedance events are defined as an event where the observed value exceeds the 95^th percentile (i.e. the intensity threshold) of the baseline state for that site). Frequency represents the number of times the duration of events exceeded the 95^th percentile of the duration of exceedance events for the baseline state for that site. Frequency has been normalised per year. ‘Change’ shows the value for the dredge period as a proportion of the baseline.</p><p>Intensity, duration and frequency (IDF) analysis of the seawater quality data at selected dredge-influenced site (Dredg.) and reference site (Ref.) for the Barrow Island, Cape Lambert and Burrup Peninsula dredging programs.</p