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The dynamic environment of natural river 昀氀oodplains creates spatial heterogeneity that in昀氀uences 昀氀oodplain functions. Diverse human activities have homogenized natural 昀氀oodplains and reduced their functions across many river networks in the temperate latitudes. Consequently, quanti昀椀cation of 昀氀oodplain heterogeneity is needed to understand patterns of spatial heterogeneity on diverse 昀氀oodplains and to inform 昀氀oodplain restoration. We use a novel approach of spatially connecting 昀椀eld and remotely sensed data in order to interpret the output of, and build upon, a previous unsupervised classi昀椀cation work昀氀ow. We apply the method to three rivers in the US Paci昀椀c Northwest and the Altamaha River in the southeastern US and compare our results to a previous study. We 昀椀nd that 昀椀eld classi昀椀cations, relative topography, and NDVI are useful for interpreting results from the unsupervised classi昀椀cation work昀氀ow. The interpretations are visually interesting, but we propose that it is the heterogeneity within the groups that is vital to 昀氀oodplain functioning. Natural 昀氀oodplains in the Paci昀椀c Northwest and coastal Southeast have moderate to high evenness, moderate to high intermixing, and moderate aggregation; and aggregation and evenness similar to rivers in Colorado and Oklahoma, USA, but lower intermixing. We attribute lower intermixing at the Altamaha River to slower rates of lateral channel migration, and lower intermixing at the Hoh River to the different hydrologic and sediment regimes and less stable braided planform. The results show that the larger rivers in this study (Altamaha, Hoh, and Sol Duc Rivers) have spatial heterogeneity similar to beaver-modi昀椀ed and shortgrass prairie rivers in Colorado, whereas the more inland and smaller river (Lookout Creek) has spatial heterogeneity similar to the tallgrass prairie site (Sand Creek). From the results of an ad hoc sensitivity analysis, we suggest using the highest spatial resolution topographic data available, using aerial imagery/mosaics from the same sensor, and removing largest patch index from the suite of comparable indices. The metrics reveal similarities and differences between rivers in the United States, and indicate that discernable trends may arise from a meta study comparing heterogeneity from more rivers across the country.
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This content will become publicly available on January 1, 2026
Finding the E-channel proton loading sites by calculating the ensemble of protonation microstates
The aerobic electron transfer chain builds a proton gradient by proton coupled electron transfer reactions through a series of proteins. Complex I is the 昀椀rst enzyme in the sequence. Here transfer of two electrons from NADH to quinone yields four protons pumped from the membrane N- (negative, higher pH) side to the P- (positive, lower pH) side. Protons move through three linear antiporter paths, with a few amino acids and waters providing the route; and through the E-channel, a complex of competing paths, with clusters of interconnected protonatable residues. Proton loading sites (PLS) transiently bind protons as they are transported from N- to P-compartments. PLS can be individual residues or extended clusters of residues. The program MCCE uses Monte Carlos sampling to analyze the E-channel proton binding in equilibrium with individual Molecular Dynamics snapshots from tra- jectories of Thermus thermuphillus Complex I in the apo, quinone and quinol bound states. At pH 7, the 昀椀ve E- channel subunits (Nqo4, Nqo7, Nqo8, Nqo10, and Nqo11) take >25,000 protonation microstates, each with different residues protonated. The microstate explosion is tamed by analyzing interconnected clusters of residues along the proton transfer paths. A proton is bound and released from a cluster of 昀椀ve coupled residues on the protein N-side and to six coupled residues in the protein center. Loaded microstates bind protons to sites closer to the P-side in the forward pumping direction. MCCE microstate analysis identi昀椀es strongly coupled proton binding amongst individual residues in the two PLS clusters.
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- PAR ID:
- 10561359
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Biochimica et Biophysica Acta (BBA) - Bioenergetics
- Volume:
- 1866
- Issue:
- 1
- ISSN:
- 0005-2728
- Page Range / eLocation ID:
- 149518
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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