Monitoring methods based on Indigenous knowledge have the potential to contribute to our understanding of large watersheds. Research in large, complex, and dynamic ecosystems suggests a participatory approach to monitoring—that builds on the diverse knowledges, practices, and beliefs of local people—can yield more meaningful outcomes than a “one-size-fits-all” approach. Here we share the results of 12 community-based, participatory monitoring projects led by Indigenous governments and organizations in the Mackenzie River Basin (2015–2018). Specifically, we present and compare the indicators and monitoring methods developed by each of these community-based cases to demonstrate the specificity of place, culture, and context. A scalar analysis of these results suggests that the combination of core (common) indicators used across the basin, coupled with others that are meaningful at local level, create a methodological bricolage—a mix of tools, methods, and rules-in-use that are fit together. Our findings, along with those of sister projects in two other major watersheds (Amazon, Mekong), confront assumptions that Indigenous-led community-based monitoring efforts are too local to offer insights about large-scale systems. In summary, a networked approach to community-based monitoring that can simultaneously engage with local- and watershed-level questions of social and ecological change can address gaps in knowledge. Such an approach can create both practices and outcomes that are useful to local peoples as well as to those engaged in basin-wide governance.
The productivity and phenology of vegetation are spatially and temporally variable ecosystem functions. Monitoring spatial–temporal patterns in these functions can improve our understanding of global change and natural ecosystem variability and inform management actions. Researchers typically focus on temporal changes within or among static regions and omit dynamics of spatial configuration. Our goal was to assess global spatial–temporal variability in productivity and phenology regimes between 2000 and 2012 using a temporally dynamic functional type classification. Fourteen functional types were defined for each year by clustering the annual sum and annual variability (seasonality) of the fraction of photosynthetically active radiation (fPAR)—a biophysical proxy for vegetation greenness or productivity—from the Moderate Resolution Imaging Spectrometer (MODIS). The fourteen functional types ranged from tundra (low cumulative fPAR and highly seasonal) to tropical forests (high cumulative fPAR and low seasonality). Variability in the mean of the fPAR metrics and in two spatial pattern metrics was assessed for each functional type. Many pixels changed from one cluster to another then back again, suggesting considerable short-term variability. Temporal variability in the mean of the fPAR metrics was relatively low, with changes instead primarily manifested in spatial pattern. Spatial pattern was most variable within tundra, grasslands, shrublands, and savannas. A dynamic classification demonstrated the variability in spatial patterns of primary productivity and can be used for future monitoring.
Abstract Repeat photography offers distinctive insights into ecological change, with ground‐based oblique photographs often predating early aerial images by decades. However, the oblique angle of the photographs presents challenges for extracting and analyzing ecological information using traditional remote sensing approaches. Several innovative methods have been developed for analyzing repeat photographs, but none offer a comprehensive end‐to‐end workflow incorporating image classification and georeferencing to produce quantifiable landcover data. In this paper, we provide an overview of two new tools, an automated deep learning classifier and intuitive georeferencing tool, and describe how they are used to derive landcover data from 19 images associated with the Mountain Legacy Project, a research team that works with the world's largest collection of systematic high‐resolution historic mountain photographs. We then combined these data to produce a contemporary landcover map for a study area in Jasper National Park, Canada. We assessed georeferencing accuracy by calculating the root‐mean‐square error and mean displacement for a subset of the images, which was 4.6 and 3.7 m, respectively. Overall classification accuracy of the landcover map produced from oblique images was 68%, which was comparable to landcover data produced from aerial imagery using a conventional classification method. The new workflow advances the use of repeat photographs for yielding quantitative landcover data. It has several advantages over existing methods including the ability to produce quick and consistent image classifications with little human input, and accurately georeference and combine these data to generate landcover maps for large areas.
Anthropogenic climate change has driven an increase in the frequency, size, and severity of fires at high latitudes. Recent research shows that increasing fire severity in the subarctic is altering the trajectories of forest succession, but to date, research on the effect of fire severity on tundra succession has been limited. In this study, we investigated short-term recovery of shrub tundra communities following fire in the Tuktoyaktuk Coastal Plain and Anderson River Plain ecoregions of the Northwest Territories. To understand the effects of fire severity, we documented vegetation and permafrost recovery within moderately burned, severely burned, and unburned portions of six tundra fires that burned in 2012. We found that vegetation structure at moderately and severely burnt sites recovered rapidly toward pre-fire levels, but that differences in community composition, characterized by a decrease in shrub and lichen cover as well as an increase in abundance of ruderals and graminoids, persisted at severely burned sites. The persistence of thermal changes and increased thaw depth indicate that while biotic recovery can occur promptly, severe fire may have long-term impacts on belowground conditions.
Abstract Remote sensing, regional ground temperature and ground ice observations, and numerical simulation were used to investigate the size, distribution, and activity of ice wedges in fine‐grained mineral and organic soils across the forest‐tundra transition in uplands east of the Mackenzie Delta. In the northernmost dwarf‐shrub tundra, ice wedge polygons cover up to 40% of the ground surface, with the wedges commonly exceeding 3 m in width. The largest ice wedges are in peatlands where thermal contraction cracking occurs more frequently than in nearby hummocky terrain with fine‐grained soils. There are fewer ice wedges, rarely exceeding 2 m in width, in uplands to the south and none have been found in mineral soils of the tall‐shrub tundra, although active ice wedges are found there throughout peatlands. In the spruce forest zone, small, relict ice wedges are restricted to peatlands. At tundra sites, winter temperatures at the top of permafrost are lower in organic than mineral soils because of the shallow permafrost table, occurrence of phase change at 0°C, and the relatively high thermal conductivity of icy peat. Due to these factors and the high coefficient of thermal contraction of frozen saturated peat, ice wedge cracking and growth is more common in peatlands than in mineral soil. However, the high latent heat content of saturated organic active layer soils may inhibit freezeback, particularly where thick snow accumulates, making the permafrost and the ice wedges in spruce forest polygonal peatlands susceptible to degradation following alteration of drainage or climate warming.
Abstract Ice‐cored permafrost landscapes are highly sensitive to disturbance and have the potential to undergo dramatic geomorphic transformations in response to climate change. The acceleration of thermokarst activity in the lower Mackenzie and Peel River watersheds of northwestern Canada has led to the development of large permafrost thaw slumps and caused major impacts to fluvial systems. Individual “mega slumps” have thawed up to 10 6 m 3 of ice‐rich permafrost. The widespread development of these large thaw slumps (up to 40 ha area with headwalls of up to 25 m height) and associated debris flows drive distinct patterns of stream sediment and solute flux that are evident across a range of watershed scales. Suspended sediment and solute concentrations in impacted streams were several orders of magnitude greater than in unaffected streams. In summer, slump impacted streams displayed diurnal fluctuations in water levels and solute and sediment flux driven entirely by ground‐ice thaw. Turbidity in these streams varied diurnally by up to an order of magnitude and followed the patterns of net radiation and ground‐ice ablation in mega slumps. These diurnal patterns were discernible at the 10 3 km 2 catchment scale, and regional disturbance inventories indicate that hundreds of watersheds are already influenced by slumping. The broad scale impacts of accelerated slumping are indicated by a significant increase in solute concentrations in the Peel River (70,000 km 2 ). These observations illustrate the nature and magnitude of hydrogeomorphic changes that can be expected as glaciogenic landscapes underlain by massive ice adjust to a rapidly changing climate.
