Arabidopsis Coordinates the Diurnal Regulation of Carbon Allocation and Growth across a Wide Range of Photoperiods

In short photoperiods, plants accumulate starch more rapidly in the light and degrade it more slowly at night, ensuring that their starch reserves last until dawn. To investigate the accompanying changes in the timing of growth, Arabidopsis was grown in a range of photoperiods and analyzed for rosette biomass, photosynthesis, respiration, ribosome abundance, polysome loading, starch, and over 40 metabolites at dawn and dusk. The data set was used to model growth rates in the daytime and night, and to identify metabolites that correlate with growth. Modeled growth rates and polysome loading were high in the daytime and at night in long photoperiods, but decreased at night in short photoperiods. Ribosome abundance was similar in all photoperiods. It is discussed how the amount of starch accumulated in the light period, the length of the night, and maintenance costs interact to constrain growth at night in short photoperiods, and alter the strategy for optimizing ribosome use. Significant correlations were found in the day- time and the night between growth rates and the levels of the sugar-signal trehalose 6-phosphate and the amino acid biosynthesis intermediate shikimate, identifying these metabolites as hubs in a network that coordinates growth with diurnal changes in the carbon supply.

Satellite Remote Sensing of Savannas:Current Status and Emerging Opportunities

Savannas cover a wide climatic gradient across large portions of the Earth’s land surface and are an important component of the terrestrial biosphere.Savannas have been undergoing changes that alter the composition and structure of their vegetation such as the encroachment of woody vegetation and increasing land-use intensity.Monitoring the spatial and temporal dynamics of savanna ecosystem structure(e.g.,partitioning woody and herbaceous vegetation)and function(e.g.,aboveground biomass)is of high importance.Major challenges include misclassification of savannas as forests at the mesic end of their range,disentangling the contribution of woody and herbaceous vegetation to aboveground biomass,and quantifying and mapping fuel loads.Here,we review current(2010–present)research in the application of satellite remote sensing in savannas at regional and global scales.We identify emerging opportunities in satellite remote sensing that can help overcome existing challenges.We provide recommendations on how these opportunities can be leveraged,specifically(1)the development of a conceptual framework that leads to a consistent definition of savannas in remote sensing;(2)improving mapping of savannas to include ecologically relevant information such as soil properties and fire activity;(3)exploiting high-resolution imagery provided by nanosatellites to better understand the role of landscape structure in ecosystem functioning;and(4)using novel approaches from artificial intelligence and machine learning in combination with multisource satellite observations,e.g.,multi-/hyperspectral,synthetic aperture radar(SAR),and light detection and ranging(lidar),and data on plant traits to infer potentially new relationships between biotic and abiotic components of savannas that can be either proven or disproven with targeted field experiments.