Utility of commercial high‐resolution satellite imagery for monitoring general flowering in Sarawak, Borneo

General flowering (GF), irregular synchronous mass flowering of multiple tree species across multiple families, is a unique biological phenomenon of the mixed lowland dipterocarp forest in Southeast Asia. Characterizing the spatial extent and temporal dynamics of GF is essential for an improved understanding of climate–vegetation interactions and the potential climate change impact on this species-rich rainforest. We investigated the utility of newly available high-temporal (daily) and high-spatial (3–4 m) resolution remote sensing by the PlanetScope commercial satellite constellation for detecting flowering trees in a dipterocarp rainforest at Lambir Hills National Park, Sarawak, Malaysia. Our study was focused on the latest GF event known to have occurred in the region in the year 2019. PlanetScope successfully acquired 13 clear-sky or minimally cloud-contaminated scenes over the park during a study period of January 1, 2019 to August 31, 2019 encompassing the 2019 GF event. In situ phenology observations verified that the PlanetScope images detected the flowering crowns of tree species that turned into white or orange. This multitemporal image dataset also captured the flowering peak and species differences. The correlation coefficients between the multitemporal image signatures and in situ phenology observations were moderate to very strong (0.52–0.85). The results indicated that the 2019 GF event was a whole-park phenomenon with the flowering peak in May. This study reports the first successful satellite-based observations of a GF event and suggests the possibility of regional-scale characterization of species-level phenology in the dipterocarp forest, key information for biodiversity conservation in Southeast Asia

Reaction dynamics analysis of an E. coli protein translation system by computational modeling

A single enzymatic reaction can often be described by Michaelis-Menten kinetics, but once reactions are connected to one other, it becomes difficult to understand and capture a complete description of the reaction dynamics due to its high dimensionality. To elucidate the dynamic features of a biologically relevant large-scale reaction network, we constructed a computational model of minimal protein synthesis consisting of 241 components and 968 reactions that synthesize the Met-Gly-Gly (MGG) peptide based on an Escherichia coli-based reconstituted in vitro translation (IVT) system [1]. We performed a simulation using parameters collected primarily from the literature and found that the rate of MGG peptide synthesis becomes nearly constant in minutes, thus achieving a steady-state similar to experimental observations. In addition, concentration changes to 70% of the components, including intermediates, reached a plateau in a few minutes. However, the concentration change of each component exhibits several temporal plateaus, or a quasi-stationary state (QSS), before reaching the final plateau. To understand the complex dynamics, we focused on whether the components reached a QSS, mapped the arrangement of components in a QSS in the entire reaction network structure and investigated time-dependent changes. We found that components in a QSS form clusters that grow over time but not in a linear fashion and that this process involves the collapse and regrowth of clusters before the formation of a final large single cluster. These observations might commonly occur in other large-scale biological reaction networks. This developed analysis might be useful for understanding large-scale enzymatic reactions, thereby extracting the characteristics of the reaction network, including phase transitions. As the reconstituted IVT has been used for various applications inducing directed evolution of membrane proteins [2,3], the developed computational model might be useful in further enhancement of the yield of synthesized proteins using the reconstituted IVT. Please click Additional Files below to see the full abstract