Seasonally ice‐covered permafrost lakes in the Arctic emit methane to the atmosphere during periods of open‐water. However, processes contributing to methane cycling under‐ice have not been thoroughly addressed despite the potential for significant methane emission to the atmosphere at ice‐out. We studied annual dissolved methane dynamics within a small (0.2 ha) Mackenzie River Delta lake using sensor and water sampling packages that autonomously and continuously collected lake water samples, respectively, for two years at multiple water column depths. Lake physical and biogeochemical properties (temperature; light; concentrations of dissolved oxygen, manganese, iron, and dissolved methane, including stable carbon, and radiocarbon isotopes) revealed annual patterns. Dissolved methane concentrations increase under‐ice after electron acceptors (oxygen, manganese, and iron oxides) are depleted or inaccessible from the water column. The radiocarbon age of dissolved methane suggests a source from recently decomposed carbon as opposed to thawed ancient permafrost. Sources of dissolved methane under‐ice include a diffusive flux from the sediments and may include water column methanogenesis and/or under‐ice hydrodynamic controls. Following ice‐out, the water column only partially mixes allowing half of the winter‐derived dissolved methane to be microbially oxidized. Despite oxidation at depth, surface water was a source of methane to the atmosphere. The greatest diffusive fluxes to the atmosphere occurred following ice‐out (75 mmol CH4m−2 d−1) and during a mixing episode in mid‐July, likely driven by a storm event. This study demonstrates the importance of fine‐scale temporal sampling to understand dissolved methane processes in seasonally ice‐covered lakes.
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Compound‐specific stable isotope analysis of individual amino acids (CSIA‐AA) has emerged as a transformative approach to estimate consumer trophic positions (TPCSIA) that are internally indexed to primary producer nitrogen isotope baselines. Central to accurate TPCSIAestimation is an understanding of beta (
β) values—the differences between trophic and source AA δ15N values in the primary producers at the base of a consumers’ food web. Growing evidence suggests higher taxonomic and tissue‐specific βvalue variability than typically appreciated.
This meta‐analysis fulfils a pressing need to comprehensively evaluate relevant sources of
βvalue variability and its contribution to TPCSIAuncertainty. We first synthesized all published primary producer AA δ15N data to investigate ecologically relevant sources of variability (e.g. taxonomy, tissue type, habitat type, mode of photosynthesis). We then reviewed the biogeochemical mechanisms underpinning AA δ15N and βvalue variability. Lastly, we evaluated the sensitivity of TPCSIAestimates to uncertainty in mean βGlx‐Phevalues and Glx‐Phe trophic discrimination factors (TDFGlx‐Phe).
We show that variation in
βGlx‐Phevalues is two times greater than previously considered, with degree of vascularization, not habitat type (terrestrial vs. aquatic), providing the greatest source of variability (vascular autotroph = −6.6 ± 3.4‰; non‐vascular autotroph = +3.3 ± 1.8‰). Within vascular plants, tissue type secondarily contributed to βGlx‐Phevalue variability, but we found no clear distinction among C3, C4and CAM plant βGlx‐Phevalues. Notably, we found that vascular plant βGlx‐Lysvalues (+2.5 ± 1.6‰) are considerably less variable than βGlx‐Phevalues, making Lys a useful AA tracer of primary production sources in terrestrial systems. Our multi‐trophic level sensitivity analyses demonstrate that TPCSIAestimates are highly sensitive to changes in both βGlx‐Pheand TDFGlx‐Phevalues but that the relative influence of βvalues dissipates at higher trophic levels.
Our results highlight that primary producer
βvalues are integral to accurate trophic position estimation. We outline four key recommendations for identifying, constraining and accounting for βvalue variability to improve TPCSIAestimation accuracy and precision moving forward. We must ultimately expand libraries of primary producer AA δ15N values to better understand the mechanistic drivers of βvalue variation.
Lampreys have a complex life cycle which includes a multi‐year infaunal larval stage (ammocoete). Gut content analysis has generally identified detritus (i.e., unidentifiable organic matter) as the major dietary component to ammocoetes, though algae can also be important. However, gut content preserves only a snapshot of the animal's diet and does not reflect assimilated material. In order to better characterise the nutritional sources supporting ammocoete growth, we analysed ammocoete body tissue and potential dietary sources at two streams using natural Δ14C and δ15N to estimate time‐integrated nutritional support. Bayesian isotope mixing models revealed differences in the importance of sources supporting ammocoetes between sites. Ammocoetes from a stream in a mixed land usage area (~50% agriculture, ~40% forest and ~10% developed) were primarily supported (mean: ~50%) by fresh terrestrial organic matter but were also supported by substantial contributions (mean: ~30%) by aged organic matter (AOM) and autochthonous material (algae; mean ~20%). In a predominantly forested (~90%) headwater stream, different modelling scenarios (uninformed or informed priors) suggested that algal support of ammocoete nutrition ranged from 7% to 45%. However, the model relying on informed priors developed from gut content analysis produced the low estimates, suggesting these were more reliable. When algae were a minor component of the nutrition at the forested site, ammocoetes were highly dependent on AOM (83 ± 26%; mean ±
SD). Based on these findings, ammocoete growth and development are predicted to be strongly influenced by both land use and the availability of allochthonous and autochthonous materials of varying ages within streams.