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Figure 14: Principal Component Analysis (PCA) Biplot of Elemental Abundances across all Samples
Lack of Association Between Gold and Common Pathfinder Elements
Lack of Association Between Gold and Common Pathfinder Elements
This analysis looks at how different elements tend to appear together in the same rock samples, which helps identify which elements move through the Earth in similar ways. Elements that plot close together on the diagram are behaving similarly, while those that are far apart are influenced by different rock altering processes (Figure 14).
One important result is that gold does not behave the way it is often expected to. Gold is commonly searched for using “indicator” elements like arsenic, mercury, and selenium which usually move with gold in mineral-forming fluids (Maciolek et al., 2002, Melo-Gómez et al., 2025). However, in this dataset, gold does not group with arsenic or mercury. Instead, gold shows a closer association with molybdenum, an element commonly linked to porphyry and epithermal mineral systems rather than ultramafic-hosted environments such as the Atlin ophiolite (Mueller & Groves, 2002). This relationship suggests that the observed pathfinder behavior is more consistent with gold signatures typical of porphyry–epithermal settings, and that arsenic and mercury do not function as reliable indicators of gold in this system. Consequently, any gold present is likely occurring at background levels and does not reflect a gold-enriched ultramafic mineralization style.
Nickel and cobalt show a strong relationship with each other, meaning they tend to occur together in the same samples. This is expected because these two elements commonly originate from the same types of rocks (Naldrett et al., 1996; Han et al., 2020) . Interestingly, mercury appears close to nickel and cobalt, indicating that mercury may act as an indicator for processes that affect nickel and cobalt, rather than for gold in this case.
Copper shows a different behaviour. Instead of grouping with other base metals, it clusters with elements that are commonly moved during rock alteration. This suggests that copper in these samples is controlled more by chemical changes in the rocks than by the same processes that affect nickel, cobalt, or zinc. Lead is especially notable because it is clearly separated from the other base metals, meaning it followed a different pathway during fluid movement and rock alteration.
Overall, these results show that there is no single “one-size-fits-all” pattern for how metals behave. In this system, traditional indicator elements for gold do not work as expected, while other metals group together in ways that reflect the original rock composition and later chemical changes. This highlights the importance of understanding the specific geological context when using chemical data to search for valuable mineral resources.
Figure 15: PCA Biplot of Elemental Abundance with Location Ellipses
Figure 16: PCA Biplot of Elemental Abundance with Rock Type Ellipses
Similarities Between Elemental Concentrations Across Location and Rock Type
Similarities Between Elemental Concentrations Across Location and Rock Type
The PCA biplots show substantial overlap between the confidence ellipses for the Anna and Pictou mine locations (Figure 15), indicating that bulk geochemical compositions are broadly similar between the two sites. Likewise, the ellipses for different rock types (dunite, serpentinite, and listwanite) overlap extensively in Figure 16, suggesting limited geochemical separation among lithologies at the whole-rock scale. Together, these patterns indicate that neither sampling location nor rock type exerts a strong control on the overall geochemical variability.
This limited spatial and lithological differentiation implies that the geochemical signal is dominated by shared processes rather than localized effects, supporting the feasibility of applying a pathfinder-element approach across the study area. Because bulk geochemistry is relatively consistent between locations and rock types, pathfinder relationships can be interpreted regionally rather than being restricted to specific sites or lithologies.
Figure 17: Correlation Table of Elemental Abundances
Elemental Correlation Patterns Revealed by Pearson Correlation Analysis
Elemental Correlation Patterns Revealed by Pearson Correlation Analysis
The correlation matrix shows that several elements vary together across the samples, indicating that they are influenced by the same controlling processes (Figure 17). Nickel and cobalt show a strong positive correlation with each other (Ni–Co, r ≈ 0.68) and are also associated with chromium (Ni–Co–Cr), suggesting that their concentrations are mainly controlled by the original rock composition rather than later fluid activity. Iron and manganese also show a strong relationship (Fe–Mn, r ≈ 0.64), along with Fe–Cr correlations, which likely reflect changes in iron-bearing minerals during rock alteration.
A second group includes zinc, copper, and lead, which are strongly correlated with one another, particularly Pb–Zn (r ≈ 0.74) and Pb–Cu (r ≈ 0.44). This pattern suggests that these metals were introduced or redistributed together, likely by the same metal-bearing fluids. Elements commonly used as indicators of fluid-related metal movement, such as arsenic and selenium, show moderate correlations with these base metals (e.g., As–Zn, r ≈ 0.76; Se–Cu, r ≈ 0.47), indicating that they track fluid activity rather than differences in the original rock type.
In contrast to the PCA results, correlation analysis indicates that gold is in fact correlated with several of its commonly expected pathfinder elements, including Hg and Se; however, these relationships are weak. Gold shows modest positive correlations with Mo (Au–Mo, r ≈ 0.22), Se (Au–Se, r ≈ 0.28), and Hg (Au–Hg, r ≈ 0.20), and no meaningful correlation with Ni or Co. Despite being present, these weak associations indicate that gold is not a major contributor to the overall geochemical structure of the dataset, which is consistent with gold occurring at background levels rather than forming part of a gold-enriched system.
Key Takeaways
Key Takeaways
Gold–pathfinder relationships: Gold does not correlate very strongly with its commonly expected pathfinder elements (e.g., As, Hg), but instead shows a modest association with Mo, suggesting that gold behavior in this dataset more closely resembles porphyry–epithermal geochemical signatures rather than ultramafic-hosted mineralization. Although this observation is likely due to the lack of significant concentrations of gold within these samples.
Nickel and cobalt behavior: Nickel and cobalt display strong positive correlations with each other and with mantle rock-related elements such as Fe, Cr, Zn, Hg, and Se. Notably, mercury also correlates with the Ni–Co association, suggesting that in this system Hg behaves as a pathfinder within the Atlin ophiolite complex's specific alteration processes rather than as an indicator of hydrothermal gold mineralization.
Listwanite outliers: Distinctive geochemical outliers, particularly elevated Ni and Co concentrations in listwanite samples, highlight localized metal enrichment during alteration; although analytically robust, these outliers require expanded sampling to determine whether they represent isolated occurrences or systematic enrichment within listwanite units.
Limited spatial and lithological variance: The strong overlap of confidence ellipses for both sampling location and rock type indicates minimal variation in bulk geochemistry across the dataset, suggesting broadly similar compositions and supporting the feasibility of applying a pathfinder-element approach regionally rather than being restricted to specific locations or lithologies.
Statistical power and limitations: The small sample size (n = 20) limits statistical power and restricts population-level inferences for the Atlin Ophiolite Complex; while repeated XRF measurements confirm that observed anomalies are real, the results should be considered exploratory rather than fully quantitative, and additional sampling is required to validate broader trends.
Conclusion
Conclusion
Overall, the results show that metal patterns in the Atlin area are mainly controlled by the original rock chemistry and how the rocks were altered over time, rather than by gold-rich mineralization. Nickel and cobalt consistently occur together and are closely linked with mercury, indicating that mercury is useful for tracking processes related to nickel and cobalt enrichment, not gold. Gold shows only weak relationships with commonly used indicator elements and appears to be present at very low levels. The similar chemical signatures across rock types and sampling locations suggest that indicator-element approaches can be applied across the region, but they are most effective for identifying nickel- and cobalt-related enrichment rather than gold. These results emphasize that exploration methods must be adapted to the specific geological setting, as indicators that work well in one environment may not be reliable in another.
Next Steps
Next Steps
1. Metal Deportment and Geometallurgy
Thin-section petrography, whole-rock geochemistry, X-ray diffraction (XRD), scanning electron microscopy (SEM), and electron microprobe analysis will be integrated to identify the mineralogical hosts of critical and pathfinder elements. These methods will be used to assess how metals are distributed among mineral phases, how they are redistributed during alteration, and how they are likely to behave during processing, providing insight into metal deportment and geometallurgical characteristics of the ultramafic-derived rocks.
2. Fluid Characterization
Fluid inclusion analysis, stable isotope studies, and microthermometry will be conducted to constrain the composition, temperature, and evolution of fluids responsible for alteration and metal transport. These data will help link observed geochemical patterns to fluid processes and clarify the physicochemical conditions under which metals were mobilized and concentrated.
3. Fieldwork at Atlin
One week of fieldwork is planned in the Atlin area during the upcoming summer, focusing on sampling and geological mapping at the historical Anna and Pictou mine sites. This work will involve documenting alteration styles, structural controls, and rock type relationships, as well as collecting representative samples to expand the dataset and validate laboratory-based interpretations.
Figure 18: Serpentinized Dunite Thin Section https://www.sciencephoto.com/media/1147392/view/serpentinized-peridotite-lm
Figure 19: Dunite Thin Section https://www.alexstrekeisen.it/english/pluto/dunite.php
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