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Abstract The United States produces more than 10 million tons of waste oils and fats each year. This paper aims to establish a new biomanufacturing platform that converts waste oils or fats into a series of value‐added products. Our research employs the oleaginous yeastYarrowia lipolyticaas a case study for citric acid (CA) production from waste oils. First, we conducted the computational fluid dynamics (CFD) simulation of the bioreactor system and identified that the extracellular mixing and mass transfer is the first limiting factor of an oil fermentation process due to the insolubility of oil in water. Based on the CFD simulation results, the bioreactor design and operating conditions were optimized and successfully enhanced oil uptake and bioconversion in fed‐batch fermentation experiments. After that, we investigated the impacts of cell morphology on oil uptake, intracellular lipid accumulation, and CA formation by overexpressing and deleting theMHY1gene in the wild typeY. lipolyticaATCC20362. Fairly good linear correlations (R² > 0.82) were achieved between cell morphology and productivities of biomass, lipid, and CA. Finally, fermentation kinetics with both glucose and oil substrates were compared and the oil fermentation process was carefully evaluated. Our study suggests that waste oils or fats can be economical feedstocks for biomanufacturing of many high‐value products. 

Abstract In this era of global environmental change and rapid regime shifts, managing core areas that species require to survive and persist is a grand challenge for conservation. Wildlife monitoring data are often limited or local in scale. The emerging ability to map and track spatial regimes (i.e., the spatial manifestation of state transitions) using advanced geospatial vegetation data has the potential to provide earlier warnings of habitat loss because many species of conservation concern strongly avoid spatial regime boundaries. Using 23 yr of data for the lek locations of Greater Prairie‐Chicken (Tympanuchus cupido; GPC) in a remnant grassland ecosystem, we demonstrate how mapping changes in the boundaries between grassland and woodland spatial regimes provide a spatially explicit early warning signal for habitat loss for an iconic and vulnerable grassland‐obligate known to be highly sensitive to woody plant encroachment. We tested whether a newly proposed metric for the quantification of spatial regimes captured well‐known responses of GPC to woody plant expansion into grasslands. Resource selection functions showed that the grass:woody spatial regime boundary strength explained the probability of 80% of relative lek occurrence, and GPC strongly avoided grass:woody spatial regime boundaries at broad scales. Both findings are consistent with well‐known expectations derived from GPC ecology. These results provide strong evidence for vegetation‐derived delineations of spatial regimes to serve as generalized signals of early warning for state transitions that have major consequences to biodiversity conservation. Mapping spatial regime boundaries over time provided interpretable early warnings of habitat loss. Woody plant regimes displaced grassland regimes starting from the edges of the study area and constricting inward. Correspondingly, the relative probability of lek occurrence constricted in space. Similarly, the temporal trajectory of spatial regime boundary strength increased over time and moved closer to the observed limit of GPC lek site usage relative to grass:woody boundary strength. These novel spatial metrics allow managers to rapidly screen for early warning signals of spatial regime shifts and adapt management practices to defend and grow habitat cores at broad scales.