Laser ablation mass spectrometry blast through detection in R.
Laser ablation mass spectrometry blast through detection in R.
复制标题
激光烧蚀质谱爆炸通过 R 中的检测。
DOI:
10.1002/rcm.9533
复制
发表时间:
2023
期刊:
影响因子:
--
通讯作者:
Searle-Barnes A
中科院分区:
文献类型:
--
作者:
Searle-Barnes A
RationaleOrganisms that grow a hard carbonate shell or skeleton, such as foraminifera, corals or molluscs, incorporate trace elements into their shell during growth that reflect the environmental change and biological activity they experienced during life. These geochemical signals locked within the carbonate are archives used in proxy reconstructions to study past environments and climates, to decipher taxonomy of cryptic species and to resolve evolutionary responses to climatic changes.MethodsHere, we use laser ablation inductively coupled plasma mass spectrometry (LA‐ICP‐MS) as a time‐resolved acquisition to quantify the elemental composition of carbonate shells and skeletons. We present theLABLASTER(Laser Ablation BLASt Through Endpoint in R) package, which imports a single time‐resolved LA‐ICP‐MS analysis, then detects when the laser has ablated through the carbonate as a function of change in signal over time and outputs key summary statistics. We provide two examples within the package: a fossil planktic foraminifer and a tropical coral skeleton.ResultsWe present the first R package that automates the selection of desired data during data reduction workflows. This is achieved by automating the detection of when the laser has ablated through a sample using a smoothed time series, followed by removal of off‐target data points. The functions are flexible and adjust dynamically to maximise the duration of the desired geochemical target signal, making this package applicable to a wide range of heterogenous bioarchives. Visualisation tools for manual validation are also included.ConclusionsLABLASTERincreases transparency and repeatability by algorithmically identifying when the laser has either ablated fully through a sample or across a mineral boundary and is thus no longer documenting a geochemical signal associated with the desired sample. LABLASTER's focus on better data targeting means more accurate extraction of biological and geochemical signals.
影响因子:
3.9
作者:
Fehrenbacher, Jennifer S.;Spero, Howard J.;Eggins, Stephen
通讯作者:
Eggins, Stephen
DOI:
10.1029/2020gc009254
发表时间:
2020
期刊:
Geosystems
影响因子:
--
作者:
Fehrenbacher, Jennifer;Marchitto, Thomas;Spero, Howard J.
通讯作者:
Spero, Howard J.
影响因子:
4.6
作者:
Chalk TB;Standish CD;D'Angelo C;Castillo KD;Milton JA;Foster GL
通讯作者:
Foster GL