Results were calculated for the distance classes i = 1, 2, 3,…,10. These species richness grids S i were combined by performing an inverse distance-weighted approach according to: $$ S_w = \sum\limits_i

= 2^10 \left( d_i^ – p \right. \cdot \left. CHEM1 \right) + S_1 $$ (1)with p > 0, d ≥ 1. S 1 is the original point-to-grid species richness grid, S w is the grid of the resulting weighted species richness and d i is the distance (d 2 = 2, d 3 = 3,…) used as a threshold in the conditional triangulation. For each distance class, the increase in species richness relative to the next smaller distance class was calculated for each quadrat and PD173074 molecular weight multiplied by a weighting term \(d_i^-p.\) Thereby, p is a tuning parameter of the weighting procedure applied to the quadrats. For each p > 0 and d ≥ 1, the corresponding weighting term lies between 0 and 1. The greater p Alvocidib in vivo becomes, the more relative weight is put on species richness calculated for smaller distances. The closer p is to 0, the more relative weight is put on species richness interpolated for larger

distances (see Appendix 2). For the present work, we selected p = 0.5, which resulted in a combination of high weights for small distances and relatively low weights for large distances. The weighted differences between the distance classes were then added to the original point-to-grid data (S 1), yielding the map of weighted species richness S w . Species richness centers were identified as contiguous areas of quadrats with S w  > 100, i.e. more than 100 interpolated species. Adjusting weighted species richness for sampling effort We addressed the impact of uneven spatial sampling effort by incorporating an additional weighting factor. This factor is based on the ratio of the number of species recorded in a quadrat and the maximum number of species reported for each

center of species richness C of the original point-to-grid map [S 1/max C (S 1)]. This relationship between the number of species in a quadrat to the respective reference quadrat is used as a proxy for sampling effort for each quadrat. The pheromone higher the relative sampling effort in a quadrat, the nearer it will be to 1, hence the smaller the weighting (1—relative sampling effort) for the respective quadrat will be (Eq. 2). The higher the weight (relative sampling effort close to 0), the larger is the fraction of the interpolated species richness that enters the final estimation of species richness for that specific quadrat. The application of this correction factor to the inverse distance-weighted sum of species richness at the distances 2–10, added to the observed point-to-grid species richness S 1 is henceforth referred to as adjusted species richness S adj. $$ S_\textadj = \left( 1 – \fracS_1 \max_C (S_1 ) \right)\,*\,\sum\limits_i = 2^10 \left( d_i^ – p \right. \cdot \left. {\left( S_i \right.