This article is taken from:

Davies, B.J., 2022. CRYOSPHERIC GEOMORPHOLOGY: Dating Glacial Landforms I: archival, incremental, relative dating techniques and age-equivalent stratigraphic markers. (link)

Dating boulder exposure age with lichens

Lichenometry, mostly using the species Rhizocarpon subgenus Rhizocarpon, has been widely used to date Late Holocene (last ~1000 years) glacial landforms, including the Northern Hemisphere “Little Ice Age” neoglaciation (Beschel, 1950; Bradwell, 2009; Bull, 2018; Garibotti and Villalba, 2017, 2009; Roberts et al., 2010; Rosenwinkel et al., 2015; Winchester and Harrison, 2000).

Lichenometry has the advantage of being inexpensive and widely applicable. This technique utilises the fact that certain lichen species are slow growing and long-lived, and grow outwards in a radial manner to form crust-like, circular patches on rocks (thalli; McCarthy, 2013). Lichens growing on boulders on moraines will typically be larger with distance from the glacier terminus, meaning that lichen size can be used as a relative measure for the amount of time that glacial debris has been exposed in a stable position, and been available for lichen colonisation and growth (McCarthy, 2013).

Data required to calculate an exposure age, typically of a glacial debris such as a boulder on a moraine, would include growth curve, sampling method, calculated moraine age, and any other relevant information.

Assumptions of lichenometry

Lichenometry makes a number of key assumptions (McCarthy, 2013; Osborn et al., 2015):

  • A surface can be no older than the oldest individual lichen (thallus) growing upon it;
  • Lichen thalli with a circular outline grew radially outwards from a central point;
  • The radial growth of lichens is sporadic, but it is constant when averaged over a longer period of time;
  • The largest lichen occupies the optimal site for growth, and is the fastest-growing lichen in the vicinity;
  • The diameter of the largest or average of the largest lichen thalli with circular outlines can be used to estimate the time elapsed since colonisation began;
  • The largest lichen colonised first, and continued to grow through the period between colonisation and observation.

Challenges include variable lichen growth rate due to substrate and microclimatic factors, variable lichen ecesis intervals (the time lag between exposure and colonisation), ambiguous thallus morphology, and potential inheritance of the largest lichens (Osborn et al., 2015). Studies of lichen mortality suggest that the largest lichen may not be representative of exposure age (ibid).

Lichenometry species

Species suitable for lichenometric dating have an ecesis time (interval between exposure and colonisation of a surface) of decades to centuries (McCarthy, 2013). Initially, there is a phase of very rapid growth, lasting a few decades, followed by a period of prolonged, steady growth that may last for centuries. Mostly, thalli belonging to the broad group Rhizocarpon geographicum agg. are targeted (McCarthy, 2013) (Figure 4).

It should be noted that this group includes several aggregated species that may have different growth rates (ibid.). However, the challenges of separating these different species in the field means that usually this is in practice ignored.

Figure 4. Map lichen – Rhizocarpon geographicum – Blefjell, Norway. Wikimedia commons

Lichenometry sampling strategies

The methods used to collect lichen data are variable among users (Bradwell, 2009). Measurement parameters can include the long axis, short axis, average diameter, largest diameter, modal frequency of lichen sizes and percentage of lichen cover. These variable sampling strategies all have an impact on the construction of lichenometric dating curves. Variations in sampling strategy has led to poor reproducibility among lichenometric studies.

The traditional approach has been to measure the largest lichen (LL) (the diameter of the largest non-competing circular thalli on a surface). Others may measure the mean of the 5 or 10 largest thalli (5LL or 10LL), in order to avoid reliance on a single, and potentially anomalous, sample (Bradwell, 2009). However, the five largest lichens may be statistical outliers and give an anomalously old surface exposure age (Bull, 2018). These lichens may be on reworked boulders with lichen thalli that began growing before their blocks were deposited in a glacial moraine.

The fixed-area largest lichen (FALL) restricts the sampling areas (usually boulders) to ~1 m2. This method assumes that lichen thalli sizes are normally distributed, and that the mean thallus size increases with exposure age (Bradwell, 2009; Bull and Brandon, 1998). This method makes an assumption about the size-frequency distribution of lichens on a surface (Bradwell, 2009) and may be subject to biases imparted by statistical treatment (Osborn et al., 2015).

The Size-Frequency approach (SF) involves the operator measuring the long axis of all thalli of a single species growing within a representative subsample of the surface (25 – 50 m2). Sample sizes of >1000 thalli are recommended (Benedict, 2009; Bradwell et al., 2006). This method measures and quantifies the size-frequency distribution of a lichen population.
The lichen cover approach (LC) assumes that the percentage of a rock covered with a single species of lichen will increase with time. This technique is more subjective and involves estimating the percentage of lichen cover, so it is only recommended when other approaches are impractical (Bradwell, 2009).

A number of papers review these different techniques, and make different recommendations (Bradwell, 2009; Bull, 2018; McCarthy, 2013; Osborn et al., 2015). Bull (2018) recommends that accurate dating of surface exposure times using lichenometry should use measures of central tendency, by obtaining large datasets of the largest lichen thallus diameter (LL) on many blocks or boulders. Users should plot histograms of the largest lichen diameter (LL) and use the histogram peaks to determine the mean largest lichen size and thus the relative (and absolute if calibrated) age of the moraine (Bull, 2018).

Lichenometry calibration curves

Lichen growth rates are spatially and temporally variable, making it challenging to construct a growth curve. Firstly, growth rates are susceptible to climatic variability. In Patagonia, for example, the strong east-west precipitation gradient introduces statistically significant differences in the growth curves (Garibotti and Villalba, 2009). This means that the site-specific calibration of lichen growth rates is required.

Secondly, lichen thalli begin growth after an ecesis time (the lag interval between exposure and colonisation) that varies between a decade or longer than a century (McCarthy, 2013), and which is frequently poorly constrained (Evans et al., 1999).

Thirdly, the growth rate of Rhizocarpon decreases over time. Growth is initially rapid, which lasts for several decades, followed by steady, linear growth that can last centuries. This makes it unfeasible to simply extrapolate growth rates from a small number of control points. In addition, there are some challenges for dating longer exposure ages, as the loss of the central part of a thallus due to weathering is common in older samples, and recolonization can make it challenging to distinguish individual thalli (ibid.).

Growth curves require, as a minimum, indices of thalli size in a known calendar year (McCarthy, 2013). However, the development of lichen growth curves remains problematic. True growth curves should involve the repeated observation of the areal growth in a marked individual thallus over time, rather than the more usual thallus size-surface age scatter plots (Osborn et al., 2015).

Quality assurance protocols

Deriving exposure ages from lichenometry remains challenging, and a number of studies may not be reproducible due to the variable methodologies employed and the assumptions made. Each sampling methodology has weaknesses, and the lack of standards and no definitive useful temporal range is very concerning (Osborn et al., 2015). Development of sampling protocols remains challenging.

Practitioners are recommended to carefully review their assumptions and sampling methodologies.

Crustose lichens remain useful as relative-age indicators, and large R. geographicum thalli may indicate that a moraine pre-dates the “Little Ice Age”, but a method for delimiting a growth curve to determine absolute ages remains challenging (Osborn et al., 2015).


Selected references and further reading

Armstrong, 2016

Beschel, R.E., 1950. Flechten als Altersmaßstab rezenter Moränen. Zeitschrift für Gletscherkunde und Glazialgeologie 1, 152-161.

Bradwell, T., Dugmore, A.J., Sugden, D.E., 2006. The little ice age glacier maximum in Iceland and the North Atlantic Oscillation: Evidence from Lambatungnajökull, southeast Iceland. Boreas 35, 61-80.

Bradwell, T., 2009. Lichenometric dating: a commentary, in the light of some recent statistical studies. Geografiska Annaler: Series A, Physical Geography 91, 61-69.

Bull, W.B., 2018. Accurate surface exposure dating with lichens. Quaternary Research 90, 1-9.

Davies, B.J., 2022. 4.12: Dating Glacial Landforms I: Archival, Incremental, Relative Dating Techniques and Age-Equivalent Stratigraphic Markers, in: Haritashya, U., Harbor, J., French, H.M. (Eds.), Treatise on Geomorphology (Second Edition): Cryospheric Geomorphology. Elsevier, pp. 225-248.

Evans, D.J.A., Archer, S., Wilson, D.J.H., 1999. A comparison of the lichenometric and Schmidt hammer dating techniques based on data from the proglacial areas of some Icelandic glaciers. Quaternary Science Reviews 18, 13-41.

McCarthy, D.P., 2013. LICHENOMETRY, in: Elias, S.A., Mock, C.J.B.T. (Eds.), Encyclopedia of Quaternary Science (Second Edition). Elsevier, Amsterdam, pp. 565-572.

Osborn, G., McCarthy, D., LaBrie, A., Burke, R., 2015. Lichenometric dating: Science or pseudo-science? Quaternary Research 83, 1-12.

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