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This study addresses the gap in understanding the diversity, species, and functional trait distribution of different algal groups that occur in the Okavango Delta (a near-pristine subtropical wetland in northwestern Botswana) across hydrological and habitat gradients. We systematically characterize the delta's algal flora, addressing the gap left by previous research that was limited to single algal groups (e.g., diatoms) and/or only looking at upstream areas in the Okavango River basin. We analyzed 130 algal samples from 49 upstream and downstream sites with higher and lower flooding frequency, respectively, across a river-to-floodplain habitat gradient. Chlorophyta and Bacillariophyta dominated both abundance and taxon richness (>80%) of the total 494 taxa found from 49,158 algal units counted (cells, colonies, coenobia, and filaments). Smaller algae were more abundant in downstream floodplains than in upstream channels and lagoons. Motile and siliceous algae were much more abundant than non-motile, nitrogen fixing, and phagotrophic algae. The frequency of these traits was associated more with flooding frequency than habitat type. The highest algal richness and diversity were found downstream, where shallow floodplain ecosystems with seasonally fluctuating water depths offer greater habitat heterogeneity, and macronutrients are resuspended. The increasing threats from upstream water abstraction plans, fracking, and climate change require enhanced protection and monitoring of the Okavango Delta's natural annual flood-pulse to maintain the high species and functional diversity of this unique wetland's microalgae. [ABSTRACT FROM AUTHOR]

The Arctic is rapidly changing, disrupting biogeochemical cycles and the processing, delivery and sedimentation of carbon (C), in linked terrestrial-aquatic systems. In this investigation, we coupled a hydrogeomorphic assessment of catchment soils, sediments and plants with a recent lake sediment sequence to understand the source and quality of organic carbon present in three Arctic upland lake catchments on Disko Island, located just south of the Low-High Arctic transition zone. This varied permafrost landscape has exposed soils with less vegetation cover at higher altitudes, and all lakes received varying extent of glacial meltwater inputs. We provide improved isotope and biomarker source identifications for palaeolimnological studies in high latitude regions, where terrestrial vegetation is at or close to its northerly and altitudinal range limit. The poorly developed catchment soils lead to lake waters with low dissolved organic carbon (DOC) concentrations (<1.5 mg L-1). Sedimentary Carbon/Nitrogen (C/N) ratios, the C isotope composition of organic matter (S13Corg) and biomarker ratios (n-alkanes, n-alkanols, n-alkanoic acids and sterols) showed that sedimentary organic matter (OM) in these lakes is mostly derived from aquatic sources (algae and macrophytes). We used a 210Pb dated sediment core to determine how carbon cycling in a lake-catchment system (Disko 2) had changed over recent centuries. Recent warming since the end of the Little Ice Age (LIA ~1860 AD), which accelerated after ca. 1950, led to melt of glacier ice and permafrost releasing nutrients and DOC to the lake, stimulating pronounced aquatic algal production, as shown by a > 10 fold increase in P-carotene, indicative of a major regime shift. Our findings highlight that in Arctic lakes with sparsely developed catchment vegetation and soils, recent Anthropocene warming results in pronounced changes to in-lake C processing and the deposition of more reactive, predominately autochthonous C, compared with extensively vegetated low Arctic systems. [ABSTRACT FROM AUTHOR]

Image segmentation is a fundamental precursor to quantitative image analysis. At present, no standardised methodology exists for segmenting images of fluorescent proxies for trace evidence. Experiments evaluated (i) whether manual segmentation is reproducible within and between examiners (with three participants repeatedly tracing three images) (ii) whether manually defining a threshold level offers accurate and reproducible results (with 20 examiners segmenting 10 images), and (iii) whether a global thresholding algorithm might perform with similar accuracy, while offering improved reproducibility and efficiency (16 algorithms tested). Statistically significant differences were seen between examiners' traced outputs. Manually thresholding produced good accuracy on average (within ±1% of the expected values), but poor reproducibility (with multiple outliers). Three algorithms (Yen, MaxEntropy, and RenyiEntropy) offered similar accuracy, with improved reproducibility and efficiency. Together, these findings suggest that appropriate algorithms could perform thresholding tasks as part of a robust workflow for reconstruction studies employing fluorescent proxies for trace evidence. [ABSTRACT FROM AUTHOR]