Sampling of environmental variables
At each drift net, flow velocity and water depth were measured three
times during base flow and three times each during the P1 and P2 phase.
The values of the three measurements were then averaged. Flow velocity
was recorded using a micro propeller (Flowatch Flowmeter) 2 cm above the
substrate surface (v0 ), at the net-center
approximately 13 cm from the substrate surface
(vnet ) and 6 cm below the water surface
(v100 ). Water depth was measured in front of each
net with a rigid meter. Concurrently, turbidity as NTU (Nephelometric
Turbidity Unit) was measured at the drift net of the central sampling
site using a portable turbidity meter (Hach Lange 2100Q). Additionally,
the extension of the dewatering
area (DAex ) as distance between the waterline at
base flow (Qbase ) and at peak flow
(Qpeak ; i.e., flow magnitude) was measured nearby
the stranding nets.
Water temperature (T ) and water level were continuously recorded
(1 min interval) using one logger (Vemco Minilog II-T, AMIRIX Systems
Inc.) and one pressure probe (DCX-22 SG/VG CTD, Keller), respectively,
placed at the upstream sampling site of each HP reach. Based on the
water level measurements, the mean and maximum up-
(URmean , UR max) and
down-ramping rates (DRmean ,DR max) were determined. Discharge data were
obtained from federal and cantonal gauging stations as well as from the
operators of the hydropower plants and were used to determineQbase , Qpeak , flow
amplitude (Qpeak - Qbase ) and
ratio (Qpeak/Qbase ). The grain
size distribution (GSD) along gravel bars of each HP reach was
determined by a representative number of line-by-number analyses (n = 1
– 3) using a gravelometer. GSD curves were determined and analyzed,
taking particle values as ‘percent finer’. Froude number (Fr ) and
bed shear stress (τb ) according to Whiting and
Dietrich (1990) were calculated for each HP sampling site.
Data analysis
Data analysis were either based on the total community or at taxa-level.
To ensure consistency and to down-weight the influence of rare taxa,
only taxa with a relative abundance > 1% over all drift,
stranding or benthic samples, were selected to express taxa-specific
responses (Appendix C in Data S1).
Additionally, to assess
trait-specific responses, we classified taxa found in the benthic
samples based on two relevant ecological trait categories related to HP
sensitivity (RHEOPHYLAX, 2021;
Schülting et al., 2021): ‘hydraulic habitat preference’ (classes:
lentic/lotic; indicating taxa adaptation to low or high current) and
‘vertical habitat preference’ (classes: interstitial/surface; indicating
taxa flow exposure; Appendix C in Data S1).
Benthic community composition and stranding were analyzed in terms of
density, expressed as the number of individuals standardized by the
sampled area (ind./m2). Single samples were pooled per
sampling site (Figure 2a) and chronological sampling (Figure 2b),
resulting in 24 and 18 composite samples respectively for each HP reach
as well as 12 benthic composite samples for each RF
reach.
MIV drift intensity was calculated following Pegel (1980) as the number
of individuals in the drift standardized by the drift-net area and the
exposure time (ind./m2min). To consider the effect of
an entire HP scenario, drift samples collected during the UR, P1, P2 and
DR phase were pooled per sampling site and HP scenario. For each HP and
RF reach this resulted in 18 composite samples each for base flow and HP
scenario. Further, since MIV drift patterns, and probably also stranding
patterns, are strongly related to the benthic source population, we
calculated the drift and stranding propensity (e.g., Bruno et al., 2013;
Timusk et al., 2016) as the drift intensity and stranding density,
respectively, standardized by the benthic density. All benthic samples
were pooled per HP reach to generate a single estimate of benthic
density at the reach scale.