Artificial light at night (ALAN) decreases plant diversity and performance in experimental grassland communities – Data on species biomass and traits
Data files
Sep 29, 2023 version files 19.44 KB
Abstract
Artificial light at night (ALAN) affects many areas of the world and is increasing globally. To date, there has been limited and inconsistent evidence regarding the consequences of ALAN on plant communities as well as the fitness of their constituent species. ALAN could be beneficial for plants as they need light as an energy source, but they also need darkness for regeneration and growth. We created model communities composed of 16 plant species sown, exposed to a gradient of ALAN ranging from ‘moonlight only’ to conditions like situations typically found directly underneath a streetlamp. We measured plant community composition and its production (biomass), as well as functional traits of three plant species from different functional groups (grasses, herbs, legumes) in two separate harvests. We found that biomass was reduced by 33% in the highest ALAN treatment compared to the control, Shannon diversity decreased by 43% and Evenness by 34% in the first harvest. Some species failed to establish in the second harvest. Specific leaf area, leaf dry matter content and leaf hairiness responded to ALAN. These responses suggest that plant communities will be sensitive to increasing ALAN, and they flag a need for plant conservation activities that consider impending ALAN scenarios.
README: Artificial light at night (ALAN) decreases plant diversity and performance in experimental grassland communities – Data on species biomass and traits
https://doi.org/10.5061/dryad.hhmgqnknt
In ALAN_specis_biomass.csv, Biomass per species in the proportion sorted is given. In ALAN_biomass.csv, the biomass of the entire Ecotron is given. In ALAN_traits.csv, traits of the species are given.
Description of the data and file structure
ALAN_specis_biomass.csv:
The species are abbreviated by 3 letters genus and species. unit describes the name of the EcoUnit (numbered consecutively), light refers to the light regime (given in lux), mass indicates the biomass (in g dry matter) and harvest denotes whether it was the first or 2nd harvest studied (categorical information).
ALAN_biomass.csv:
biomass refers to biomass (g dry matter), unit describes the name of the EcoUnit (numbered consecutively), and harvest denotes whether it was the first or 2nd harvest studied. Treatment refers to the light regime (in lux).
ALAN_traits.csv:
Species and EcoUnit are given as above. Treatment refers to the light regime (in lux).. Hair density is hairiness (hairs mm-2), besides that toughness (N mm-1), contact angle (CA_Mean, °), fresh weight (g), dry weight (g), leaf area (cm2), specific leaf area (SLA; cm2 g-1), leaf dry matter content (mg g-1), SPAD, plant height (cm) and the chlorophyll parameters FvFm and PIabs are given as described in Methods.
Methods
The EcoUnits were filled with 1.23 m3 of unsterilised, well-mixed soil from the vicinity of the EcoTron, as we also monitored soil communities in the same experimental setup (see Cesarz et al.). Plant communities comprising 16 plant species were sown into soil on 19 February 2020 (see Table S1). Because the soil was not sterilised, some of the local seed bank was also transferred into our experiment. Plant communities were harvested by clipping aboveground plant biomass (2 cm above topsoil) on June 11, July 3, and August 28 (establishment period), as well as on October 27 and December 8 (measurement period). This harvest regime mimics typical intensive grassland management in central Europe, with short growth phases in between harvest events.
For this study, we analysed the last two harvests in detail to address temporal variations and accumulated effects of the ALAN treatment (see Table S1; hereafter referred to harvest 1 and 2, respectively). The harvests differed in length: harvest 1 encompassed a time for regrowth of 9 weeks, whereas harvest 2 only encompassed 6 weeks, as this was embedded in a bigger experimental setup. The biomass of one-eighth (0.19 m2) of each EcoUnit (subplot) was separated into species (both sown and not sown as well as ‘unknown’) and then dried to constant weight at 60°C for three days. Plant identification was sometimes not possible when the plants were not fully mature. These species were all clustered as ‘unknown species’, whereas for others only the genus could be determined. Dead biomass was also recorded. Plant functional trait data was collected for one species each per functional group of grasses (B. hordeaceus), non-legume forbs (P. lanceolata) and legumes (T. repens) just before the harvests in October and December. The species were selected based on their frequent occurrence in the EcoUnits. However, not all plant traits were measured on all species and in all EcoUnits. P. lanceolata was originally not sown into the communities but had become one of the dominant species in the EcoUnits by October and was thus selected for our experiment. It was not very abundant by the end of the experiment as it did not regenerate well after the harvest in October. All traits were collected and measured just before the harvest unless stated otherwise. Stretched plant height of three representative individuals per species and EcoUnit was measured using a ruler. Then, ten healthy leaves from at least three manually randomly selected individuals per species and EcoUnit were harvested and transported to the laboratory, where SLA, LDMC, toughness, hairiness and wettability were measured.
All ten leaves were scanned on an Epson Expression 11000 XL scanner and the resulting images were analysed using ImageJ to determine the leaf area. In the case of T. repens, only the lamina was scanned. Leaves were weighed and subsequently dried at 70°C for at least 48h, and dry weight was recorded to calculate SLA (leaf area of fresh leaf/ dry weight) and LDMC (dry weight/ fresh weight). All weights were measured using a precision scale (QUINTIX315_1S, Sartorius Lab Instruments GmbH & Co. KG, Goettingen, Germany). A few days afterwards, the chlorophyll fluorescence measurements and the SPAD values were determined on living plants in the EcoUnits, just before the harvests. The hairiness, or rather the density of trichomes, of the leaves was analysed by counting the hairs from an image taken at 400-fold magnification using a light microscope and focussing on the middle part of the leaf (Ocular 10x/22, Di-Li-2009, Distelkamp-Electronic, Kaiserslautern, Germany) in ImageJ. For that, four of the leaves used in SLA measurements were chosen at random. Hairs were counted on the upper and lower leaf side and then added to make a total for both leaf sites. T. repens did not show any hair on its lamina. The samples of this species were excluded from the subsequent analysis. The leaf thickness was measured with a digital caliper (WEZU Messwerkzeuge Remscheid GmbH, Remscheid, Germany) at the same spot as leaf toughness. For leaf toughness, the puncture resistance was measured using a surgical blade at a speed of 129 mm min-1 on an electric test stand (Sauter GmbH, Wutöschingen, Germany) and the force of the cut was measured with a power meter (FH 50, Sauter GmbH). The leaf toughness was than calculated as the quotient between the puncture resistance and the thickness. The leaf wettability was investigated via measuring the contact angle (CA) of a water droplet and the leaf, where high CA means low wettability. For that, a droplet of 5 µl distilled water was placed on a flat leaf surface for 90 seconds and then photographed (Nikon D5300 with a Sigma DC Objective, Chiyoda, Tokyo, Japan). The CA was then measured using ImageJ. Chlorophyll fluorescence was measured using a PocketPEA device (Hansatech, King’s Lynn, Norfolk, UK). We measured the parameters PIabs as well as plant stress via Fv/Fm after 30 min of dark adaption to ensure a full reduction of the photosystems on three replicate individuals for each EcoUnit and species. These measurements were not performed on P. lanceolata, as not many individuals were abundant after harvesting the leaves for the previous analysis. The SPAD value was measured using a SPAD 502 (Minolta Camera Co., Osaka, Japan) on the same individual. For each individual, three replicate measurements were performed as the values varied within individuals.