Far from Naturalness: How Much Does Spatial Ecological Structure of European Tree Assemblages Depart from Potential Natural Vegetation?

Abstract

Contemporaneous plant communities may retain a mark of past disturbances in their ecological patterns. However, unraveling the history of disturbance on natural systems at a large scale is often unfeasible, due to the complexity of the factors involved and lack of historical data. Here we aim at demonstrating how comparing observed spatial structure of tree assemblages with that expected in a hypothetical, undisturbed scenario can shed light on how natural European forests are. Borrowing an analytical approach developed in the field of network analysis, we assessed how much the observed ecological patterns of nestedness (i.e. positive co-occurrence), segregation (i.e. negative co-occurrence), and modularity in tree assemblages deviate from randomness, and from those projected by Potential Natural Vegetation (PNV) geobotanical expert assessments. We found clear evidence that European forests are far from a natural condition, showing only moderate signals (especially at higher latitudes) of the ecological spatial structure typical of undisturbed vegetation (i.e. nestedness). Our results highlight how taking into account spatial structure along with diversity can be a fundamental tool to address this problem and assess the degree of naturalness in species assemblages.

Fig 1. Explanation of the moving window approach used to build species/area matrices and to geo-reference structural values.

The window consisted of a regular square grid of 100 cells (each having size 0.1° latitude × 0.1° longitude). The window was moved across all of Europe by displacements of 0.1° latitude or longitude at a time. At each repositioning, the window was superimposed on both ACV_T and PNV_T distribution maps in order to create two species × site matrices.

Fig 2. Difference in spatial ecological structure between ACV_T and PNV_T.

Relationships between $\stackrel{-}{Ɲ}$, Z-score and modularity values computed for ACV_T and the corresponding values computed for PNV_T in all 1° latitude × 1° longitude matrices. Diagonal lines of equality provide a visual guide for seeing whether ACV_T or PNV_T had the greater value.

Fig 3. Mapping the structure of ACV_T and PNV_T at 1° latitude × 1° longitude resolution.

$\stackrel{-}{Ɲ}$, Z and modularity values computed in all 1° latitude × 1° longitude matrices for both ACV_T and PNV_T. Red pixels in mid panels correspond to matrices having Z>2, which indicates significance of $\stackrel{-}{Ɲ}$ at p<0.05.

Fig 4. Mapping the structure of ACV_T and PNV_T across European eco-regions.

$\stackrel{-}{Ɲ}$, Z and modularity values computed in all 1° latitude × 1° longitude matrices for both ACV_T and PNV_T, averaged per eco-region.