“…The methodology used to obtain an atlas of geochemical natal signatures and for establishing the natal origin of the recruits is described in 61 . In brief, this methodology consisted of growing early laboratory-produced mussel embryos for 6 days inside incubators deployed in the field until a larval shell had clearly developed (70 to 140 μm shell length).…”
Section: Methodsmentioning
confidence: 99%
“…Given the expected larval and juvenile growth rates at the temperature recorded during the study period (June-July of 2013), the time window of larval incubation should coincide with the period when the sampled recruits were produced. Larval shells and the larval portion of the recruits’ shells were then subjected to LA-ICPMS analysis using standard protocols (see 61 for detailed methodology). Figure 1 Map of larval incubation stations and juvenile sampling sites.…”
Marine larval dispersal is a complex biophysical process that depends on the effects of species biology and oceanography, leading to logistical difficulties in estimating connectivity among populations of marine animals with biphasic life cycles. To address this challenge, the application of multiple methodological approaches has been advocated, in order to increase confidence in estimates of population connectivity. However, studies seldom account for sources of uncertainty associated with each method, which undermines a direct comparative approach. In the present study we explicitly account for the statistical uncertainty in observed connectivity matrices derived from elemental chemistry of larval mussel shells, and compare these to predictions from a biophysical model of dispersal. To do this we manipulate the observed connectivity matrix by applying different confidence levels to the assignment of recruits to source populations, while concurrently modelling the intrinsic misclassification rate of larvae to known sources. We demonstrate that the correlation between the observed and modelled matrices increases as the number of observed recruits classified as unknowns approximates the observed larval misclassification rate. Using this approach, we show that unprecedented levels of concordance in connectivity estimates (r = 0.96) can be achieved, and at spatial scales (20–40 km) that are ecologically relevant.
“…The methodology used to obtain an atlas of geochemical natal signatures and for establishing the natal origin of the recruits is described in 61 . In brief, this methodology consisted of growing early laboratory-produced mussel embryos for 6 days inside incubators deployed in the field until a larval shell had clearly developed (70 to 140 μm shell length).…”
Section: Methodsmentioning
confidence: 99%
“…Given the expected larval and juvenile growth rates at the temperature recorded during the study period (June-July of 2013), the time window of larval incubation should coincide with the period when the sampled recruits were produced. Larval shells and the larval portion of the recruits’ shells were then subjected to LA-ICPMS analysis using standard protocols (see 61 for detailed methodology). Figure 1 Map of larval incubation stations and juvenile sampling sites.…”
Marine larval dispersal is a complex biophysical process that depends on the effects of species biology and oceanography, leading to logistical difficulties in estimating connectivity among populations of marine animals with biphasic life cycles. To address this challenge, the application of multiple methodological approaches has been advocated, in order to increase confidence in estimates of population connectivity. However, studies seldom account for sources of uncertainty associated with each method, which undermines a direct comparative approach. In the present study we explicitly account for the statistical uncertainty in observed connectivity matrices derived from elemental chemistry of larval mussel shells, and compare these to predictions from a biophysical model of dispersal. To do this we manipulate the observed connectivity matrix by applying different confidence levels to the assignment of recruits to source populations, while concurrently modelling the intrinsic misclassification rate of larvae to known sources. We demonstrate that the correlation between the observed and modelled matrices increases as the number of observed recruits classified as unknowns approximates the observed larval misclassification rate. Using this approach, we show that unprecedented levels of concordance in connectivity estimates (r = 0.96) can be achieved, and at spatial scales (20–40 km) that are ecologically relevant.
“…Ocean acidification (OA) is the decrease in ocean pH, due to the uptake of anthropogenic CO 2 from the atmosphere. Once dissolved into seawater, CO 2 increases the concentration of bicarbonate ions ([HCO 3 − ]) and lowers the pH and concentration of the carbonate ion ([CO 3 2− ]) (Gattuso and Hansson 2011). In addition to this change in the carbonate equilibrium reaction, the availability of ions will also be affected (Millero et al 2009).…”
Section: Introductionmentioning
confidence: 99%
“…Currently, there are two primary areas in which this information is applied: population connectivity and paleoclimate reconstructions. Variations in multiple trace elements in bivalve shells, gastropod statoliths, and fish otoliths have been used to infer dispersal histories, population connectivity and stock structure, a technique known as trace elemental fingerprinting (,Gomes et al ; Kroll et al ). Among climate researchers, there is also interest in the use of the elemental composition of CaCO 3 structures as proxies to reconstruct environmental conditions such as temperature, salinity or pH at their time and location of formation (Poulain et al , Immenhauser et al ).…”
mentioning
confidence: 99%
“…To date the majority of research has focused on the impact of OA on the incorporation of trace elements into foraminiferal tests (Yu et al , Henehan et al ). Bivalves, however, are more frequently used in trace elemental fingerprinting studies (Dunphy et al ; Gomes et al ). The aim of this study was, therefore, to answer the question “how will predicted future ocean Perna canaliculus formed under current CO 2 ( p CO 2 ) affect the incorporation of trace elements into the shell of Greenshell™ mussels Perna canaliculus ?.” We explore implications of p CO 2 on both elements that have been used for elucidating dispersal histories and those elements used to reconstruct geological history.…”
We sought to determine how pCO2 will affect the incorporation of trace elements into bivalve shell. This was to validate that under high pCO2 conditions reconstruction of animal movements is still viable; and to investigate potential trace element proxies for ocean carbonate chemistry. Here, we examined shell of the bivalve Perna canaliculus formed under current CO2 (pCO2 = 400 μatm) conditions and those predicted to exist in 2100 (pCO2 = 1050 μatm). Seventeen trace element:calcium ratios were examined at two locations within shells. Elements that are typically most useful in determining connectivity patterns (e.g., Sr, Mn, Ba, Mg, B) were not affected by pCO2 in shell produced early in individual's lives. This suggests that the effects of ocean acidification on dispersal signatures may be dampened. However, cobalt, nickel, and titanium levels were influenced by pCO2 consistently across shells suggesting their role as potential indicators of CO2 level.
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