Welcome to PhytCore, the open online phytolith database platform.

PhytCore was created as an archaeological tool (Albert et al., 2016). From the beginning, PhytCore has aimed to help researchers recognize and name phytoliths using modern reference plants that can be later compared to archaeologically recovered phytoliths. The identification of phytoliths as direct evidence of plants in archaeological sites or archaeologically related sites is crucial to better understand human-plants interaction (Albert, et al. 1999; Albert, et al, 2000; Albert & Weiner, 2001; Albert, et al. 2003; Tsartsidou et al., 2007; Alonso-Eguíluz et al., 2017; Esteban et al; 2017; Esteban et al., 2018; Toffolo et al., 2018; Rodríguez-Cintas et al., 2020 & Weiner et al., 2020), but also to reconstruct past landscapes and environmental conditions in particular time-periods (Kurmann, 1985; Piperno, 1989; Barboni et al., 1999; Horrocks et al., 2000; Barboni et al.; 2007 & Neumann et al., 2009; Dickau et al., 2013 & Albert et al., 2015).

The term phytolith derives from the Greek and means “plant stone”. This term has traditionally been used to refer to particles produced by biomineralization processes in higher plants (Piperno, 1988; 2006). Silica phytoliths (opal, SiO 2 · nH 2 O) are produced by living plants.

Plants take up monosilicic acid (Si(OH) 4 ) from the soil along with water and other minerals and distribute it throughout the aerial parts of the plant via xylem. Specific transporters allow silicon (Si) to exit the xylem, which is then distributed to leaf tissues by the transpiration stream and deposited as silica (SiO 2 · nH 2 O) when water evaporates from the leaf surface (Yoshida et al; 1962). Silica is deposited in a wide range of plant tissues: roots, stems, leaves and inflorescences (Jones et al., 1963; Rosen & Weiner, 1994). For nucleation and growth to occur, biomineral formation requires a localized zone (a physical bounding geometry) that achieves and maintains sufficient supersaturation (Weiner & Dove, 2003). The first locations to silicify are specialized epidermal cells, such as hairs, papillae, and short cells. Three main places where silica is deposited are recognized, the cell wall, the cell lumen and in intercellular spaces (Hodson, 2016; Kumar et al.; 2017).

Phytolith chemistry depends on the cellular environment. For example, while in “cell wall phytoliths” silica is deposited in a carbohydrate matrix that gives the silica some order, “lumen phytoliths” are expected to contain more organic molecules (Hodson, 2016).

Phytolith production is influenced by genetic patterns, ecological conditions, and silica availability (Piperno, 1988, 2006). Not all plants produce phytoliths in the same amounts. For example, while monocot plants are rich in phytoliths, the wood of dicot plants produces very few phytoliths, and sometimes none (Albert & Weiner 2001; Tsartsidou et al., 2007). That is why, when performing modern phytolith benchmark studies, quantitative analyses should also be carried out to better understand phytolith production in each plant studied, considering plant types and different environmental conditions (Albert et al., 1999; Albert & Weiner, 2001; Albert et al., 2003 & Tsartsidou et al., 2007). In archaeological contexts, this information is essential, both to identify anthropogenic contributions of plants in a given context, and to determine in what proportion each plant or plant component is represented.

As phytoliths reproduce the cellular tissue of different plant components, a single plant can produce different phytolith morphotypes. This is called multiplicity (Rovner, 1971; Vrydaghs et al., 2016). The association of different characteristic morphotypes of certain plants is crucial to better define the plant provenience. Similar plants can produce similar morphotypes. This is called redundancy (Rovner, 1971; Vrydaghs et al., 2016). The use of morphometric and/or SEM approaches combined with statistical tools (Pearsall et al., 1995; Ball et al., 1999; Berlin et al., 2003; Portillo et al., 2006; Ball et al., 2016, & Ball et al., 2017) has helped for many years to better discriminate between different plants. More recently, other approaches such as the use of confocal microscope (Gallaher et al., 2020) or Deep learning are being considered to overcome this aspect.

Phytcore accepts the FAIR data principles (Findable, Accessible, Interoperable and Reusable) to promote maximum use of research data (Wilkinson et al., 2016) in phytolith studies. PhytCore platform aims to enable a systemic change of science practices to Open Science in archaeology.