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In fire-suppressed landscapes, managers make difficult decisions about devoting limited resources for prescribed fire. Using GIS-based multicriteria decision analysis, we developed a model assessing ecological need for prescribed fire on Michigan’s state-owned lands, ranging from fire-dependent prairies, savannas, barrens, and oak and pine forests to fire-intolerant mesic forests, and including a diversity of wetlands. The model integrates fine-scale field-collected and broad-scale GIS data to identify where prescribed fire needs are greatest. We describe the model’s development and architecture, present results at multiple scales, introduce the concepts of “fire gaps” and “fire sink”, and rate the fire needs of more than 1.8 million hectares into one of six fire needs classes. Statewide, fire needs increase with decreasing latitude. The highest and lowest needs occur in southwestern Michigan and the Upper Peninsula, respectively, but actual fire application rates for these regions are inverted. The model suggests burn rates should be increased 2.2 to 13.4 times to burn all lands with greater than high fire needs. The model identifies regional patterns; highlights specific sites; and illustrates the disparity of fire needs and fire application. The modeling framework is broadly applicable to other geographies and efforts to prioritize stewardship of biodiversity at multiple scales.

As more is learned about glycoproteins’ roles in human health and disease, the biological functionalities of N-linked glycans are becoming more relevant. Protein deglycosylation allows for the selective release of N-glycans and facilitates glycoproteomic investigation into their roles as prebiotics or anti-pathogenic factors. To increase throughput and enzyme reusability, this work evaluated several immobilization methods for an endo-β-N-acetylglucosaminidase recently discovered from the commensal Bifidobacterium infantis. Ribonuclease B was used as a model glycoprotein to compare N-glycans released by the free and immobilized enzyme. Amino-based covalent method showed the highest enzyme immobilization. Relative abundance of N-glycans and enzyme activity were determined using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Kinetic evaluation demonstrated that upon immobilization, both Vmax and the Km decreased. Optimal pH values of 5 and 7 were identified for the free and immobilized enzyme, respectively. Although a higher temperature (65 vs. 45 °C) favored rapid glycan release, the immobilized enzyme retained over 50% of its original activity after seven use cycles at 45 °C. In view of future applications in the dairy industry, we investigated the ability of this enzyme to deglycosylate whey proteins. The immobilized enzyme released a higher abundance of neutral glycans from whey proteins, while the free enzyme released more sialylated glycans, determined by nano-LC Chip Q-ToF MS.