The overall aims of MrPARTS was to improve understanding of plant functioning in real word settings by developing technical solutions to the difficulty in making frequent, phenology (seasonal cycle)-relevant measurements of roots.
Currently, ecosystem scientists are able to collect data at daily or better timescale on changes in above-ground portions of ecosystems by using remote sensed images (from satellites, aircraft, or local static cameras). This is of use as short-term changes (such as the beginning of leaf growth) can be related to measurements of carbon dioxide exchange by the ecosystem and helps us gain a mechanistic understanding of how ecosystems function.
Roots make up a substantial proportion of total plant biomass and we know that the amount and function of roots changes both over time and in response to background conditions such as climate or soil fertility. As all biomass is made of carbon, this affects the overall C storage and fluxes in and out of the ecosystem. However, roots are often overlooked as measurements are very difficult, usually requiring excavation and cleaning before measurements can be made. Consequently we often assume that roots are predictable from shoot measurements in such experiments (which are used to inform future climate change predictions) without knowing if this assumption is correct. Understanding how true this assumption is, and how different environmental conditions change this link, is key to predicting whole-ecosystem changes in the future.
Thus the scientific/technical objectives of MrPARTS were:
1) develop a set of affordable (and hence replicable on experimental budgets) automated minirhizotrons to capture images of root growth at phenological timescales
2) develop a method of analysing frequent root images to extract ecologically useful information
3) deploy these systems in a mesocosm experiment to test basic mechanistic controls on high time resolution root dynamics and their links to above-ground processes
4) deploy these systems at a field site (Majdas del Tietar, in Extremadura Spain) where both a nutrient manipulation experiment and strong seasonal variability in water availability may drive desychronisation above-and-below ground, and where above-ground data is already being collected
5) collect ancillary validation data to 'ground truth' automatically extracted data from minirhizotron imagery.
