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Kolle, O.

Publications and source records attributed to Kolle, O..

2 recordsLinked to original sources

Plant diversity stabilizes soil temperature

Extreme weather events are occurring more frequently, and research has shown that plant diversity can help mitigate impacts of climate change by increasing plant productivity and ecosystem stability1,2. Although soil temperature and its stability are key determinants of essential ecosystem processes related to water and nutrient uptake3 as well as soil respiration and microbial activity4, no study has yet investigated whether plant diversity can buffer soil temperature fluctuations. Using 18 years of a continuous dataset with a resolution of 1 minute ([~]795,312,000 individual measurements) from a large-scale grassland biodiversity experiment, we show that plant diversity buffers soil temperature throughout the year. Plant diversity helped to prevent soil heating in hot weather, and cooling in cold weather. Moreover, this effect of plant diversity increased over the 18-year observation period with the aging of experimental communities and was even stronger under extreme conditions, i.e., on hot days or in dry years. Using structural equation modelling, we found that plant diversity stabilized soil temperature by increasing soil organic carbon concentrations and, to a lesser extent, by increasing the plant leaf area index. We suggest that the diversity-induced stabilization of soil temperature may help to mitigate the negative effects of extreme climatic events such as soil carbon release, thus slow global warming.

ecology↗

GO WIDE TO GO DEEP: AFFORDABLE, REPLICABLE ROBOTIC MINIRHIZOTRON SAMPLING FOR PHENOLOGY STUDIES

Automating dynamic fine root data collection in the field is a longstanding challenge with multiple applications for co-interpretation and synthesis for ecosystem understanding. High frequency root data are only achievable with paired automated sampling and processing. However, automatic minirhizotron (root camera) instruments are still rare and data is often not collected in natural soils nor analysed at high temporal resolution. Instruments must also be affordable for replication and robust under variable natural conditions. Here, we show a system built with off-the-shelf parts which samples at sub-daily resolution. We paired this with a neural network to analyse all images collected. We performed two mesocosm studies and two field trials alongside ancillary data collection (soil CO2 efflux, temperature and moisture content, and PhenoCam-derived above-ground dynamics. We produce robust daily time-series of root dynamics under all conditions. Temporal root changes were a stronger driver than absolute biomass on soil CO2 efflux in mesocosm. Proximal sensed above ground dynamics and belowground from minirhizotron data were not synchronised. Root properties extracted were sensitive to soil moisture and occasionally to time of day (potentially relating to soil moisture). This may only affect high frequency imagery and should be considered in interpreting such data. HIGHLIGHTCompletely automatic root dynamics with method transferrable between field settings.

ecology↗