Denitrification in large tropical river systems is likely important for nitrogen retention estimates, but is limited by the need for measurements and the ability to scale these estimates to relate seasonal changes to river geomorphology and discharge. Geomorphic units (GUs), that describe the structure of a river system based on their inundation frequency and vegetation cover, may be useful to characterise features that influence denitrification rates. In this study, we tested the hypothesis that measurements of potential denitrification rate (PDR) using denitrification enzyme assays from different GUs could be used to1) relate PDR to soil, vegetation and different land use and land-cover (LULC) types as controlling factors and 2) that these characteristics could be assessed using remote sensing data to model PDR over a large spatial scale (along a 50 km reach) for the Padma River (Bangladesh). Specifically, 245 PDR measurements were made from the four LULC types with in eight GUs during the dry/winter season 2020. Linear regression using a mixed-modelling approach showed that PDR was highly related to vegetation cover and soil moisture across all GUs. Sentinel-2 data were then used to develop relationships between the Normalised Difference Vegetation Index. (NDVI) and vegetation cover and, specifically, between Sentinel-2 band 11 and soil moisture, which also reasonably described PDR rates. We then used this satellite data to estimate reach-scale PDR in post-monsoon, dry/winter and pre-monsoon seasons. The satellite-based model showed that PDR increased in GUs from post-monsoon 2019 to pre-monsoon 2020. The vegetation islands and the bars were the most important GUs for denitrification in all seasons. The satellite-assisted approach developed in this study can be applied to the GUs in large lowland rivers where inundation occurs frequently.

Geomorphic classification of large rivers identifies morphological patterns, as a foundation for estimating biogeochemical and ecological processes. In order to support the modelling of in-channel nutrient retention or export, the classification of geomorphic units (GUs) was done in the Padma River, Bangladesh, a large and geomorphically-complex lowland river. GUs were classified using the normalized difference vegetation index (NDVI) four times over a year, so as to cover the seasonal variation of water flows. GUs were categorized as primary and secondary channels (C & S); longitudinal bar (L); transverse bar (T); side bar (SB); unvegetated bank (EK); dry channel (ED); island (VI); and water depression (WD). All types of GUs were observed over the four distinct annual seasons, except ED, which was absent during the high flow, monsoon season. Seasonal variation of the surface area of GUs and discharge showed an inverse relation between discharge and exposed surface areas of VI, L, T, and SB. Nutrients mainly enter the river system through water and sediments, and during monsoon, the maximum portion of emergent GUs were submerged. Based on the assumption that nutrient retention is enhanced in the seasonally inundated portions of GUs, nutrient retention-/export-relevant geomorphic units (NREGUs) were identified. Seasonal variation in the area of NREGUs was similar to that of GUs. The mean NDVI values of the main identified NREGUs were different. The variation of NDVI values among seasons in these NREGUs resulted from changes of vegetation cover and type. The variation also occurred due to alteration of the surface area of GUs in different seasons. The changes of vegetation cover indicated by NDVI values across seasons are likely important drivers for biogeochemical and ecological processes.

Knowledge of trophic structure is important to understand sources and pathways of energy resources in community ecology and to identify determinants of ecosystem changes. Yet, little is known from rivers of African savanna receiving large inputs of terrestrial organic matter and nutrients by large mammalian herbivores. We used Stable Isotope (δ¹³C and δ¹⁵N) Bayesian Ellipses in R (SIBER) and Layman's community-wide metrics to describe seasonal variation in trophic niches and trophic structures in midorder river reaches in the Mara River (Kenya) that differed in environmental conditions (agricultural vs. forested) and amounts of organic matter and nutrients (low vs. high inputs by livestock and hippopotami, Hippopotamus amphibius). These analyses were supplemented with data on the trophic diversity of macroinvertebrate functional feeding groups (FFGs) and fish trophic guilds. The δ¹³C and δ¹⁵N of basal resources and consumers differed between sites and changed with seasons. Sites in agricultural areas that were utilised by livestock and a site with hippopotami had higher δ¹³C than the forested site due to the presence of C4 carbon from egestion and excretion by the grazers. The forested site recorded the most taxon-rich and trophic-diverse invertebrate community, suggesting both autochthonous and allochthonous sources of energy were available. Agricultural sites and the site with hippopotami recorded high abundances of collector taxa in response to large inputs of organic matter. Fish trophic guilds were less diverse and were dominated by insectivores. The food web at the forested site had the widest trophic niche size and highest isotopic trophic diversity compared to sites in areas with large mammalian herbivores. Invertebrate and fish trophic niche sizes changed according to food resources varying with space and time. Invertebrates had higher δ¹³C values during the dry season. In contrast, fish showed higher δ¹³C values during the wet season, and trophic niche sizes were constricted and considerably overlapping, suggesting feeding on a narrow range of food sources with high trophic redundancy. This study showed that increased terrestrial organic matter by large mammalian herbivores affected trophic diversity and niche sizes for aquatic consumers in rivers draining the African savanna. Linking the density of terrestrial large mammalian herbivores to aquatic ecosystem structure and function could help manage their populations sustainably.