A diatom dataset and diatom-salinity inference model for southeast Australian estuaries and coastal lakes

Abstract

To quantify the relationship between diatom species assemblages and the water chemistry of southeast Australian estuaries and coastal lakes, a new dataset of 81 modern diatom samples and water chemistry data was created. Three hundred and ninetynine species from 53 genera were identified in 36 samples from 32 coastal water bodies in eastern Tasmania and 45 samples from 13 coastal water bodies in southern Victoria. Multivariate statistical analyses revealed that the sampling sites were primarily distributed along salinity and nutrient gradients, and that salinity, nitrate ? nitrite, phosphate and turbidity explained independent portions of variance in the diatom data. Species salinity optima and tolerances were determined and a diatom-salinity inference model (WAinv r 2 = 0.72, r 2 jack = 0.58, RMSEP = 0.09 log ppt) was developed. This new information on diatom species' salinity preferences provides a useful tool for quantitatively reconstructing salinity changes over time from diatom microfossils preserved in the sediments of a range of estuaries and coastal lakes in southeast Australia. This is valuable for studies investigating long-term human impacts and climate change in the region.

Low-resolution Australasian palaeoclimate records of the last 2000 years

“…The most common approach for characterising modern proxy-limnology-climate relationships in Australia is the "calibration in space" of lake-and wetland-derived proxies, for which lakes across an environmental gradient are sam- pled for the purpose of identifying these relationships (Gell, 1997;Saunders, 2011). In addition, "calibration in time" has been performed, whereby a proxy time series is calibrated with instrumental meteorological time series data to produce a predictive transfer function for quantitative reconstruction beyond the calibration period (Larocque-Tobler et al, 2011;von Gunten et al, 2012;Cook et al, 1994).…”

“…Transfer functions, developed from modern calibration data sets, have been established for numerous aquatic variables in both estuarine (Logan and Taffs, 2013;Tibby and Taffs, 2011) and lacustrine settings. Variables include conductivity and salinity (Barr, 2010;Barr et al, 2014;Gell, 1997;Saunders et al, 2007Saunders et al, , 2008Saunders, 2011), pH (Tibby et al, 2003), and nutrients (Logan and Taffs, 2013;Tibby, 2004). Detailed studies on short timescales have examined pre-European baselines and anthropogenic impact since European settlement in the 19th century through pH (Taffs et al, 2008), salinity, and nutrient (Saunders et al, 2008) reconstructions.…”

Effect of artificial macrocosms on water characteristics and benthic diatom communities in Donghu Lake, China

“…For example, studies have shown that diatom species composition and distribution are influenced by a series of environmental factors, including water pH, electrical conductivity (EC), amount of dissolved oxygen (DO), temperature, light, substrate type, and presence of chlorophyll a (Chl a) (Reavie & Smol 2001;Saunders 2011;Stewart & Lamoureux 2012;Yang 2012). Thus, understanding the relationship between various environmental conditions and the resultant diatom community composition has important applications, including for water quality management and biodiversity conservation.…”

Diatoms as indicators of ecological change in freshwater reservoirs of South East Queensland

“…Diatom research in Australia to date has focussed on temperate regions and been conducted in marine and estuarine environments (Blinn and Bailey 2001b, Parr et al 2004, Saunders and Taffs 2009, Grinham et al 2011, Saunders 2011, Logan and Taffs 2013 and freshwater (rivers, lakes and reservoirs) systems (Chessman 1986, Chessman et al 1999, Tibby 2001, Chessman et al 2007, Fluin et al 2010, Hembrow and Taffs 2012, Barr et al 2013, Oeding and Taffs 2015. Chessman et al (2007) developed a diatom species index for Australian rivers (DSIAR) in south eastern Australian Rivers.…”

“…Several studies have developed transfer functions for conductivity (Ryves et al 2002, Tibby and Reid 2004, Saunders 2011 Ryves et al (2002) was considerably larger (24 -4072 µS/cm). Ryves et al (2002) found that limited historical measured conductivity fell within the error range of the developed model, and trends were similar to other paleolimnological studies in the region.…”