Periodic vegetation patterns (PVP) arise from the interplay between forces that drive the
growth and mortality of plants. Inter-plant competition for resources, in particular water,
can lead to the formation of PVP. Arid and semi-arid ecosystems may be under threat due
to changing precipitation dynamics driven by macroscopic changes in climate. These regions
display some noteable examples of PVP, for example the “tiger bush” patterns found in West
Africa.
The morphology of the periodic pattern has been suggested to be linked to the resilience of
the ecosystem (Mander et al., 2017; Trichon et al., 2018). Using remote sensing techniques,
vegetation patterns in these regions can be studied, and an analysis of the resilience of the
ecosystem can be performed.
The pyveg package implements functionality to download and process data from Google Earth
Engine (GEE), and to subsequently perform a resilience analysis on the aquired data. PVP
images are quantified using network centrality metrics. The results of the analysis can be
used to search for typical early warning signals of an ecological collapse (Dakos et al., 2008).
Google Earth Engine Editor scripts are also provided to help researchers discover locations of
ecosystems which may be in decline.
pyveg is being developed as part of a research project looking for evidence of early warning
signals of ecosystem collapse using remote sensing data. pyveg allows such research to be
carried out at scale, and hence can be an important tool in understanding changing arid and
semi-arid ecosystem dynamics. An evolving list of PVP locations, obtained through both
literature and manual searches, is included in the package at pyveg/coordinates.py. The
structure of the package is outlined in Figure 1, and is discussed in more detail in the following
sections
