Too Hot to Handle: Unprecedented Seagrass Death Driven by Marine Heatwave in a World Heritage Area

The increased occurrence of extreme climate events, such as marine heatwaves (MHWs), has resulted in substantial ecological impacts worldwide. To date metrics of thermal stress within marine systems have focussed on coral communities, and less is known about measuring stress relevant to other primary producers, such as seagrasses. An extreme MHW occurred across the Western Australian coastline in the austral summer of 2010/2011, exposing marine communities to summer seawater temperatures 2‐5 °C warmer than average. Using a combination of satellite imagery and in situ assessments, we provide detailed maps of seagrass coverage across the entire Shark Bay World Heritage Area (ca. 13,000 km2) before (2002, 2010) and after the MHW (2014, 2016). Our temporal analysis of these maps documents the single largest loss in dense seagrass extent globally (1,310 km2) following an acute disturbance. Total change in seagrass extent was spatially heterogenous, with the most extensive declines occurring in the Western Gulf, Wooramel Bank and Faure Sill. Spatial variation in seagrass loss was best explained by a model that included an interaction between two heat stress metrics, the most substantial loss occurring when degree heat weeks (DHWm) was ≥ 10 and the number of days exposed to extreme sea surface temperature during the MHW (DaysOver) was ≥ 94. Ground‐truthing at 622 points indicated that change in seagrass cover was predominantly due to loss of Amphibolis antarctica rather than Posidonia australis, the other prominent seagrass at Shark Bay. As seawater temperatures continue to rise and the incidence of MHWs increase globally, this work will provide a basis for identifying areas of meadow degradation, or stability and recovery; and potential areas of resilience

Species-specific SNP arrays for non-invasive genetic monitoring of a vulnerable bat

Abstract Genetic tagging from scats is one of the minimally invasive sampling (MIS) monitoring approaches commonly used to guide management decisions and evaluate conservation efforts. Microsatellite markers have traditionally been used but are prone to genotyping errors. Here, we present a novel method for individual identification in the Threatened ghost bat Macroderma gigas using custom-designed Single Nucleotide Polymorphism (SNP) arrays on the MassARRAY system. We identified 611 informative SNPs from DArTseq data from which three SNP panels (44–50 SNPs per panel) were designed. We applied SNP genotyping and molecular sexing to 209 M. gigas scats collected from seven caves in the Pilbara, Western Australia, employing a two-step genotyping protocol and identifying unique genotypes using a custom-made R package, ScatMatch. Following data cleaning, the average amplification rate was 0.90 ± 0.01 and SNP genotyping errors were low (allelic dropout 0.003 ± 0.000) allowing clustering of scats based on one or fewer allelic mismatches. We identified 19 unique bats (9 confirmed/likely males and 10 confirmed/likely females) from a maternity and multiple transitory roosts, with two male bats detected using roosts, 9 km and 47 m apart. The accuracy of our SNP panels enabled a high level of confidence in the identification of individual bats. Targeted SNP genotyping is a valuable tool for monitoring and tracking of non-model species through a minimally invasive sampling approach

Remotely Monitoring Change in Vegetation Cover on the Montebello Islands, Western Australia, in Response to Introduced Rodent Eradication

<div><p>The Montebello archipelago consists of 218 islands; 80 km from the north-west coast of Western Australia. Before 1912 the islands had a diverse terrestrial fauna. By 1952 several species were locally extinct. Between 1996 and 2011 rodents and cats were eradicated, and 5 mammal and 2 bird species were translocated to the islands. Monitoring of the broader terrestrial ecosystem over time has been limited. We used 20 dry-season Landsat images from 1988 to 2013 and estimation of green fraction cover in nadir photographs taken at 27 sites within the Montebello islands and six sites on Thevenard Island to assess change in vegetation density over time. Analysis of data averaged across the 26-year period suggests that 719 ha out of 2169 ha have increased in vegetation cover by up to 32%, 955 ha have remained stable and 0.6 ha have declined in vegetation cover. Over 492 ha (22%) had no vegetation cover at any time during the period analysed. Chronological clustering analysis identified two breakpoints in the average vegetation cover data occurring in 1997 and 2003, near the beginning and end of the rodent eradication activities. On many islands vegetation cover was declining prior to 1996 but increased after rodents were eradicated from the islands. Data for North West and Trimouille islands were analysed independently because of the potential confounding effect of native fauna being introduced to these islands. Mala (<i>Lagorchestes hirsutus</i>) and Shark Bay mice (<i>Pseudomys fieldi</i>) both appear to suppress native plant recruitment but not to the same degree as introduced rodents. Future research should assess whether the increase in vegetation cover on the Montebello islands is due to an increase in native or introduced plants.</p></div

Percentage vegetation cover on Trimouille Island with linear regression shown for each time period and rainfall between 1987 and 2012.

<p>Percentage vegetation cover on Trimouille Island with linear regression shown for each time period and rainfall between 1987 and 2012.</p

Percentage vegetation cover on North West Island with linear regression for each time period and rainfall between 1987 and 2012.

<p>Percentage vegetation cover on North West Island with linear regression for each time period and rainfall between 1987 and 2012.</p

Parameter estimates for the independent variables year and rainfall in each of the time periods identified via chronological clustering analysis.

<p>Level of significance: ***<0.001; **0.001; *0.01.</p><p>Parameter estimates for the independent variables year and rainfall in each of the time periods identified via chronological clustering analysis.</p

Foliage cover trend map of the Montebello island archipelago for years 1987–2012.

<p>Foliage cover trend map of the Montebello island archipelago for years 1987–2012.</p

Time line of management activities on the Montebello islands since 1995 (5, 6, 7).

<p>Time line of management activities on the Montebello islands since 1995 (5, 6, 7).</p

Regression equations used to calibrate i35 vegetation index with field measures of vegetation cover on 4 Montebello islands and Thevenard Island.

<p>Regression equations used to calibrate i35 vegetation index with field measures of vegetation cover on 4 Montebello islands and Thevenard Island.</p