Schwörer et al. Early human impact (5000 – 3000 BC) affects mountain forest dynamics in the Alps
Supporting Information Appendix S1: Direct gradient analysis
Methods
To quantify the effect of fire and grazing on the vegetation composition and diversity, we used
redundancy analysis (RDA; Ter Braak & Prentice 1988; Lepš & Šmilauer 2003; Legendre & Birks 2012) to
assess how much of the variance in the dataset can be explained by independent environmental
variables, following Colombaroli et al (2009). We used microscopic charcoal influx (a proxy for regional
fire activity, see e.g. Whitlock & Larsen 2002; Conedera et al. 2009) and Sporormiella influx (a proxy for
grazing activity by herbivores, see e.g. Cugny et al. 2010; Baker et al. 2013; Etienne et al. 2013) as
explanatory variables for vegetation changes as identified with the pollen data. We used the sample age
as a covariable in all the analyses, since a preliminary RDA showed a significant correlation between the
sample age and the pollen data (p < 0.001, RDA with sample age as the only explanatory variable and
Monte Carlo permutation test). To quantify the impact of a single explanatory variable, we performed a
RDA with only one constrained canonical axis and age as covariable (“hybrid redundancy analysis”, hRDA;
Ter Braak & Šmilauer 2002). To identify delayed reactions of the vegetation to both fire and grazing, we
also performed the analyses at different time lags (lag 0 – lag +10, corresponding to max. 290 years after
a fire). DE-PRI was included as isolines of species richness in the hRDA-biplot using a LOESS smoother to
indicate the association of plant taxa, grazing and fire with biodiversity.
Results
The redundancy analysis (RDA) shows a significant effect of fire or grazing on the vegetation data at lag 0
(Table S1). Together, the environmental variables are able to explain a small portion of the variance of
the whole dataset (5.3%, sum of all canonical eigenvalues, p=0.018). Microscopic charcoal influx alone is
highly significant and explains 4.4% (p=0.004) whereas Sporormiella influx is not significant and explains
only 0.8 % of the variance in the dataset (hRDA, Table 2, Fig. 8). hRDA at different time lags reveals that
microscopic charcoal influx has a significant effect on the vegetation at lag 0 to lag +9 (ca. 0 – 270 years
after a fire) and explains up to 8.1% of the variance in the dataset (lag +2, 60 years after a fire; Table S1).
RDA with both fire and grazing as environmental variables is significant at all lags, with the exception of
Schwörer et al. Early human impact (5000 – 3000 BC) affects mountain forest dynamics in the Alps
lag +7. Grazing alone, as expressed through Sporormiella influx, never has a significant effect on the
vegetation (Table S1). The hRDA-biplot (Fig. S3) shows a close correlation between fire, grazing and
Rumex alpinus-t. (dock), a plant typical for high-nutrient conditions found in e.g. resting places of cattle.
The second (unconstrained) axis of the hRDA explains 29.8 % and shows a bipartition between closed
forest vegetation (A. alba and P. cembra) and open or disturbed vegetation with Herbs (Poaceae,
Heracleum sphondylium) and P. abies. The isolines of evenness-detrended palynological richness (DEPRI) indicate that pollen taxa of open or disturbed environments are related to a high biodiversity (Fig.
S3). This is confirmed by a simple linear regression that shows a significant positive link of DE-PRI with
the sum of all herbaceous taxa (R2=0.21, p<0.001). However, also pollen taxa of closed natural forests
such as A. alba and P. cembra are related to a high biodiversity.