bioRxiv Science⌕ Search

Biology subjects

Strube, M.

Publications and source records attributed to Strube, M..

2 recordsLinked to original sources

Water Stress Induces Diel Patterns of Root Growth

Growth and death of vegetation control both the amount of carbon held in living biomass and much of the flow between the atmosphere and soils, the largest terrestrial carbon reservoir. However, long-term field datasets on belowground growth dynamics are rare. Knowledge is lacking on how root growth patterns relate to the environment, fluctuating carbon and water availability, and internal plant physiological control, at both seasonal and diel scales. We imaged roots using automated minirhizotrons and interpreting root length density (RLD) automatically twice a day for nine months in a temperate grassland. From winter to autumn, we always observed some root growth in individual images, but with decreasing net RLD (indicative of net turnover) becoming predominant later in the season. Roots grew day-round except during a period of about one month in spring when root growth was only in daytime. This was a period without rain, during which soil moisture depleted rapidly, but not at its driest point. We discuss potential causes for both overall and short-term growth patterns, particularly the change in drivers of growth from internal storage to new photosynthates, or limits imposed by water availability - both soil moisture and rainfall - under shifting environmental conditions.

plant biology↗

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↗