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Publication version for the revised article in Methods in Ecology and Evolution Full Changelog: https://github.com/SPATIAL-Lab/BITS/compare/v.0.9.3...v.0.9.4 

Abstract. Plant wax n-alkane chain length distribution and isotopeshave been studied in modern ecosystems as proxies to reconstruct vegetationand climate of the past. However, most paleo-proxies focus on eitherconcentrations or isotopes, whereas both carry complementary information onthe mixing sources. We propose a multi-source mixing model in a Bayesianframework that evaluates both chain length distributions and isotopessimultaneously. The model consists of priors that include user-definedsource groups and their associated parametric distributions of n-alkaneconcentration and δ13C. The mixing process involves newlydefined mixing fractions such as fractional leaf mass contribution (FLMC)that can be used in vegetation reconstruction. Markov Chain Monte Carlo isused to generate samples from the posterior distribution of these parametersconditioned on both data types. We present three case studies from distinctsettings. The first involves n-C27, n-C29, and n-C31 alkanes in lake surface sediments of Lake Qinghai, China. The model provides more specific interpretations on the n-alkane input from aquatic sources than the conventional Paq proxy. The second involves n-C29, n-C31, and n-C33 alkanes in lake surface sediments in Cameroon, western Africa. Themodel produces mixing fractions of forest C3, savanna C3, andC4 plants, offering additional information on the dominant biomescompared to the traditional two-end-member mixing regime. The third couplesthe vegetation source model to a hydrogen isotope model component, usingbiome-specific apparent fractionation factors (εa) toestimate the δ2H of mean annual precipitation. By leveraging chain length distribution, δ13C, and δ2H data offour n-alkane chains, the model produces estimated precipitation δ2H with relatively small uncertainty limits. The new framework shows promise for interpretation of paleo-data but could be further improved by including processes associated with n-alkane turnover in plants, transport,and integration into sedimentary archives. Future studies on modern plantsand catchment systems will be critical to develop calibration datasets thatadvance the strength and utility of the framework. 

Strontium isotope ratios (⁸⁷Sr/⁸⁶Sr) of incrementally grown tissues have been widely used to study movement ecology and migration of animals. However, the time scale of⁸⁷Sr/⁸⁶Sr incorporation from the environment into tissue and how it may influence data interpretation are still poorly understood. Using the relocation of a zoo elephant (Loxodonta africana) named Misha, we characterise and model the⁸⁷Sr/⁸⁶Sr turnover process using high‐resolution measurements of its tusk dentine. We seek to develop a framework that can improve quantitative interpretation of⁸⁷Sr/⁸⁶Sr data in tissues.

The⁸⁷Sr/⁸⁶Sr transition associated with the relocation is measured using laser ablation inductively coupled plasma mass spectrometry (LA‐ICP‐MS) on a prepared tusk slab. We develop a turnover model (BITS), with a rapidly exchanging central pool and a slowly exchanging peripheral pool, in a Bayesian statistical framework. The measured dentine data are first used to calibrate model parameters. The parameters are then used to estimate possible⁸⁷Sr/⁸⁶Sr input time series from two datasets via model inversion: a fidelity test using Misha's dentine data and a case study using published dentine measurements from an Alaskan Woolly Mammoth (Mammuthus primigenius).

The LA‐ICP‐MS data are consistent with a two‐compartment turnover process with equivalent half‐lives of 41 days for the central pool and 170 days for the peripheral pool. The model inversion shows good fidelity when estimating the intake⁸⁷Sr/⁸⁶Sr time series associated with Misha's relocation. In the case study, the model suggests an abrupt pattern of change in, and a much wider range of, intake⁸⁷Sr/⁸⁶Sr values than expressed in the woolly mammoth dentine data themselves.

Our framework bridges the gap between environmental⁸⁷Sr/⁸⁶Sr variation and data measured in tusk dentine or other incrementally grown tissues. It could be coupled with movement models and additional isotope tracers to study seasonal residency or the spatial and temporal patterns of movement/migration. The generic turnover processes can be adapted to other isotope systems, additional incremental tissues, or other organisms, thus expanding our modelling toolkit to investigate niche partitioning, life history traits and behavioural patterns in conservation biology, archaeology and paleoecology.