Mesozooplankton and phytoplankton time series of the Baltic Monitoring Program (BMP)

Within the monitoring programme of the Helsinki Commission (HELCOM) the mesozooplankton of the Bornholm Basin (ICES subdivision 25, station BMP-K2) was sampled by the WP-2 net (lOOfJm) 5-8 times a year in 1988-1992. Abundance, biomass, secondary production and productivity (P/B) were given for mesozooplankton groups and copepod species. Environmental factors recorded were temperature, chlorophyll a and primary production. Within copepods, the dominant species were Temora longicornis and Pseudocalanus minutus with yearly peak values of 40-50% of the monthly copepod numbers and biomasses. The annual production of Temora longicornis was highest (6.5g C/m**2/y). The biomass of all copepods was at its maximum in June (mean = 2.25g C/m**2), especially in 1992 (3.65g C/m**2). The differences between results from two methods used to calculate the production of copepods were greatest in June and July. The cladocerans were only important in summer and the appendicularians only in spring. The productivity (P/B) of the appendicularians was highest of all mesozooplankton groups. Numbers and the biomass of the meroplankton were one or two orders of magnitude below the holoplanktic groups.

(Table 1) Comparison of dive duration and speed of Adélie penguins (Pygoscelis adeliae) equipped with internal and external devices

Bio-logging studies suffer from the lack of real controls. However, it is still possible to compare indirect parameters between control and equipped animals to assess the level of global disturbance due to instrumentation. In addition, it is also possible to compare the behaviour of free-ranging animals between individuals equipped with different techniques or instruments to determine the less deleterious approach. We instrumented Adelie Penguins (Pygoscelis adeliae) with internal or external time-depth recorders and monitored them in parallel with a control group during the first foraging trip following instrumentation. Foraging trip duration was significantly longer in the internally-equipped group. This difference was due to a larger number of dives, reflecting a lower foraging ability or a higher food demand, and longer periods of recovery at the surface. These longer recovery periods were likely to be due to a reduced efficiency to ventilate at the surface, probably because the implanted devices pressurised adjacent organs such as air sacs. Moreover, descent and ascent rates were slightly lower in externally-equipped penguins, presumably because external instrumentation increased the bird drag. Looking at our results, implantation appears more disadvantageous - at least for short-term deployment - than external equipment in Adelie Penguins, while this method has been described to induce no negative effects in long-term studies. This underlines the need to control for potential effects due to methodological aspects in any study using data loggers in free-ranging animals, to minimise disturbance and collect reliable data.

Undergrowth removal in Salgesch: Soil volumetric water content and temperature time series, hourly time resolution, 2010-2015

In the Salgesch forest in the Canton of Valais in Switzerland, the understory has been removed to test whether effects on pine tree vitality. The data set published here compromises 120 time series of 60 soil temperature and 60 volumetric water content (VWC) sensors (EC-TM and 5-TM) (Decagon Devices, WA, USA) at three soil depth levels (5, 30, 60 cm) employed in the direct vicinity of six control trees and six trees with the undergrowth removed. At the levels 5 and 60 cm, three replications were made whereas 4 replications were made at level 30 cm. Six loggers recorded hourly data since 2010 with 18% gaps or 11% when not considering winter months December, January and February. The figure attached to this repository shows the average VWC and temperature of all measurements within the same depth and treatment specific setting aggregated in a defined time interval and period. In addition to that, the standard deviations are plotted as transparent polygons. In case of insufficient values for calculating standard deviations, the setting specific mean standard deviation of the considered time period are inserted.