Extended growing season lengths under climatic warming suggest increased time for plant growth. However, research has focused on climatic impacts to the timing or duration of distinct phenological events. Comparatively little is known about impacts to the relative time allocation to distinct phenological events, for example, the proportion of time dedicated to leaf growth versus senescence. We use multiple satellite and ground-based observations to show that, despite recent climate change during 2001 to 2020, the ratio of time allocated to vegetation green-up over senescence has remained stable [1.27 (± 0.92)] across more than 83% of northern ecosystems. This stability is independent of changes in growing season lengths and is caused by widespread positive relationships among vegetation phenological events; longer vegetation green-up results in longer vegetation senescence. These empirical observations were also partly reproduced by 13 dynamic global vegetation models. Our work demonstrates an intrinsic biotic control to vegetation phenology that could explain the timing of vegetation senescence under climate change.

Climate change has the potential to alter hydrological regimes and to expand saturated areas in permafrost environments, which are important sources of organic carbon. The sources, transfer zones, and delivery mechanisms of carbon into the stream network are controlled by the morphometric properties of the catchment; however, the utility and limitations of these properties as predictors of dissolved organic carbon concentrations have rarely been systematically evaluated. This study tested the relationships between 18 morphometric indicators and observed dissolved organic carbon (DOC) concentrations in the Stordalen catchment, Sweden. Geospatial and explorative statistics were combined to assess the topographical, areal, and linear indicators influencing the distribution of DOC in the catchment. The results suggest that catchment morphometric indicators can be used as proxies to predict DOC concentrations along a longitudinal continuum in subarctic climate regions (R² up to 0.52). Morphometry indicators that best served as predictors of DOC concentration in the model were as follows: relief, slope length and steepness factor (LS‐factor), sediment transport capacity, and catchment area. Due to the influence that catchment form exerts in DOC spatial patterns and processing, a morphometric approach can serve as a first approximation of DOC spatial patterns within a catchment. The initial step in identifying carbon sources based on the catchment topography has the potential to allow for quick and multilevel comparison within and between catchments.

Drainage networks delineated from Digital Elevation Models (DEMs), are the basis for the modelling of geomorphological and hydrological processes, biogeochemical cycling, and water resources management. Besides providing effective models of water flows, automatically extracted drainage networks based on topography can diverge from reality to varying degrees. The variability of such disagreement within catchments has rarely been examined as a function of the heterogeneity of land cover, soil type, and slope in the catchment of interest. This research gap might not only substantially limit our knowledge of the uncertainty of hydrological prediction, but can also cause problems for users attempting to use the data at a local scale. Using 1:100000 scale land cover maps, Quaternary deposits maps, and 2 m resolution DEMs, it is found that the accuracy of delineated drainage networks tends to be lower in areas with denser vegetation, lower hydraulic conductivity, and higher erodibility. The findings of this study could serve as a guide for the more thoughtful usage of delineated drainage networks in environmental planning, and in the uncertainty analysis of hydrological and biochemical predictions. Therefore, this study makes a first attempt at filling the knowledge gap described above.

Rivers are pivotal in the global carbon cycle, transporting terrestrial carbon to the ocean while emitting significant amount of to the atmosphere. However, the partitioning of fluvial inorganic carbon (IC) between downstream transport and atmospheric evasion remains uncertain due to intricate hydrodynamic and biogeochemical processes. Inspired by Budyko's hydrological work, this study introduces a dimensionless framework to identify critical factors in fluvial IC partitioning: the IC fraction in equilibrium with the atmosphere and the ratio of advection to evasion timescales. River catchment analyses and modeling reveal that the equilibrium ratio determines the fraction of IC stably transported downstream. The hydrodynamic‐driven timescale ratio determines the fate of out‐of‐equilibrium IC, with low‐order streams favoring atmospheric evasion and higher‐order streams promoting downstream transport. This framework provides a simple yet robust approach to predicting river carbon dynamics, with implications for land‐to‐ocean transport, fluvial emissions, and climate mitigation strategies such as enhanced weathering.