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Abstract Channel networks are important landscape features that transport water, sediment, and nutrients. Their emergence and evolution are controlled by the competition between hillslope and fluvial processes on landscapes. Investigating the geomorphic and topologic properties of these networks is crucial for quantifying the roles of processes in creating distinct patterns of channel networks and developing models to predict the network dynamics under changing environment. Here, we study the response of landscapes to changing climatic forcing via numerical‐modeling and the topographic analysis of natural landscapes. We use a physically‐based numerical landscape evolution model to investigate the channel network structure for varying hillslope and fluvial processes represented by different magnitudes of soil transport () and fluvial incision () coefficients. We show that landscapes with the same Péclet number (defined as the ratio of the timescales of advective (fluvial) to diffusive (hillslope) processes) and thus the same characteristic length scale may exhibit different geomorphic and topologic characteristics. Specifically, increasingDandK(mimicking humid conditions) or decreasingDandK(mimicking dry conditions), while keeping the same Péclet number, results in distinct branching structures. These changes lead to an exponential decrease in relief under humid conditions and an increase under dry conditions. For smaller and combinations, higher number of branching channels is observed, whereas for larger and combinations, higher number of side‐branching channels is obtained. These results align with topographic analysis of natural landscapes, suggesting that varying climatic conditions imprint distinct signatures on the branching structure of channel networks. 

Abstract Riverbed elevations play a crucial role in sediment transport and flow resistance, making it essential to understand and quantify their effects. This knowledge is vital for various fields, including river engineering and stream ecology. Previous observations have revealed that fluctuations in the bed surface can exhibit both multifractal and monofractal behaviors. Specifically, the probability distribution function (PDF) of elevation increments may transition from Laplace (two‐sided exponential) to Gaussian with increasing scales or consistently remain Gaussian, respectively. These differences at the finest timescale lead to distinct patterns of bedload particle exchange with the bed surface, thereby influencing particle resting times and streamwise transport. In this paper, we utilize the fractional Laplace motion (FLM) model to analyze riverbed elevation series, demonstrating its capability to capture both mono‐ and multi‐fractal behaviors. Our focus is on studying the resting time distribution of bedload particles during downstream transport, with the FLM model primarily parameterized based on the Laplace distribution of increments PDF at the finest timescale. Resting times are extracted from the bed elevation series by identifying pairs of adjacent deposition and entrainment events at the same elevation. We demonstrate that in cases of insufficient data series length, the FLM model robustly estimates the tail exponent of the resting time distribution. Notably, the tail of the exceedance probability distribution of resting times is much heavier for experimental measurements displaying Laplace increments PDF at the finest scale, compared to previous studies observing Gaussian PDF for bed elevation. 

Abstract Dinitrogen (N2) fixation represents a key source of reactive nitrogen in marine ecosystems. While the process has been rather well-explored in low latitudes of the Atlantic and Pacific Oceans, other higher latitude regions and particularly the Indian Ocean have been chronically overlooked. Here, we characterize N2 fixation and diazotroph community composition across nutrient and trace metals gradients spanning the multifrontal system separating the oligotrophic waters of the Indian Ocean subtropical gyre from the high nutrient low chlorophyll waters of the Southern Ocean. We found a sharp contrasting distribution of diazotroph groups across the frontal system. Notably, cyanobacterial diazotrophs dominated north of fronts, driving high N2 fixation rates (up to 13.96 nmol N l−1 d−1) with notable peaks near the South African coast. South of the fronts non-cyanobacterial diazotrophs prevailed without significant N2 fixation activity being detected. Our results provide new crucial insights into high latitude diazotrophy in the Indian Ocean, which should contribute to improved climate model parameterization and enhanced constraints on global net primary productivity projections. 

Major coastal upwelling systems are among the most productive marine ecosystems in the world. They contribute disproportionately to the cycling of carbon and nutrients in the ocean and influence marine biogeochemistry beyond their productive regions. Characterized by intense microbial respiration (both aerobic and anaerobic), major coastal upwelling systems are also hotspots for the production and outgassing of potent greenhouse gases (GHG) such as CO2, N2O, and CH4. Quantifying and understanding these roles in the context of a changing climate is therefore a subject of great interest. Here we provide a short synthesis of the current knowledge of the contributions of major coastal upwelling systems to the cycling of GHG. Despite variations within and among different systems, low-latitude coastal upwelling systems typically act as a net carbon source to the atmosphere, while those at higher latitudes function as weak sinks or remain neutral regarding atmospheric CO2. These systems also significantly contribute to oceanic N2O and CH4 emissions, although the extent of their contribution to the latter remains poorly constrained. We also overview recent and future changes to upwelling systems in the context of a warmer climate and discuss uncertainties and implications for GHG production. Although rapid coastal warming is anticipated in all major coastal upwelling systems, the future changes in upwelling-favorable winds and their implications within the context of increased stratification are uncertain. Finally, we examine the major challenges that impede our ability to accurately predict how major coastal upwelling systems will respond to future climate change, and present recommendations for future research to better capture ongoing changes and disentangle natural and forced variability.