## 1 Introduction  
In northern deltaic minerotrophic wetland ecosystems, ecotones represent important hydro-ecological transition zones where vegetation height and cover vary from open water to marsh to wet meadow and/or water-tolerant shrub species along local elevation gradients [1, 2, 3, 4]. Local upland areas (e.g., levees) that surround river channels have deeper aerated soils where less water-tolerant conifer (e.g., _Picea mariana_, _Larix laricina_, etc.) and deciduous (_Acer_ spp., _Populus tremuloides_ Michx., etc.) trees establish taller canopy woodland ecosystems [5, 6, 7, 8, 9, 10]. Local terrain and groundwater gradients are a determining factor in establishing the spatial patterns of vegetation type, cover and height zonation across such environments, with seasonal and long-term variations influenced by hydro-climatic conditions [8, 9]. Aquatic-, herbaceous-, and shrub-dominated ecotones at the margins of wetlands are also susceptible to interannual climate variability and therefore also alter their extent relative to local limiting [11]. Meanwhile, the slower growth associated with dryland forest ecosystems means that changes in woodland ecotones tend to be associated either with episodic mortality events (ecotone contraction or forest cover loss, e.g., [PERSON] et al. [12] and [PERSON] et al. [13]) or longer-term successional growth processes (ecotone expansion, e.g., [PERSON] et al. [14], [PERSON] and [PERSON] [15], [PERSON] et al. [16]). Quantification of ecotone change requires long-term monitoring. However, field data necessary for understanding the characteristics of northern ecosystem changes [17] have largely been limited due to the broad spatial extent and high deployment costs associated with these remote and in many instances inaccessible northern wetlands [18]. To address these issues, remote sensing approaches, particularly through the multi-decade Landsat program, have become necessary for studying trends in vegetation indices (VIs) as they prove consistent coverage multiple times per year over large areas. Two indices, the Normalized Difference Vegetation Index (NDVI) [19] and the Enhanced Vegetation Index (EVI) [20; 21] have been used to quantify trends in northern ecosystem change [22; 23; 24; 25]. Higher positive VI values are typically interpreted as healthier or denser vegetation cover [26; 27], thus providing a means to track wetland ecotone structure or extent change trajectories. NDVI, an indicator of photosynthetic activity [19], has been widely applied in northern, low-biomass environments impacted by climate change [28; 29], though it is also influenced by factors such as soil exposure, topography and atmospheric conditions, which can alter, offset or mask the vegetation signal [30; 31]. NDVI tends to saturate in dense or multi-layered vegetated canopies with a leaf area index (LAI) greater than 3 [32; 33], and its performance varies by land cover and growth stage [31]. EVI is widely used instead of NDVI in many scenarios due to its reduced potential for saturation and adjustment for non-linear soil influences on pixel spectral characteristics and the inclusion of a blue band to counteract the effects of the atmosphere [34; 35]. These make the index particularly resilient in areas with high soil visibility or dense canopy cover [34], though it remains sensitive to the same geometric and surface reflection variations that influence NDVI [36]. Characterization and quantification of how VI values relate to properties of vegetation height and cover, and over time, and how VI trends relate to canopy growth, ecotone expansion or dieback within boreal wetland complexes have not been systematically examined. Understanding these VIs and their relationship with vegetation height and cover (indicators of productivity) for a range of wetland and adjacent landcover classes is important as this will aid in the interpretation of NDVI and EVI trends across deltaic wetland environments and other similar northern landscapes, where global landcovers are undergoing dramatic rates of change [37; 38].