Improving Wetland Characterization with Multi-Sensor, Multi-Temporal SAR and Optical/Infrared Data Fusion

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Identification of woodland vernal pools with seasonal change PALSAR data for habitat conservation

Woodland vernal pools are important, small, cryptic, ephemeral wetland ecosystems that are vulnerable to a changing climate and anthropogenic influences. To conserve woodland vernal pools for the state of Michigan USA, vernal pool detection and mapping methods were sought that would be efficient, cost-effective, repeatable and accurate. Satellite-based L-band radar data from the high (10 m) resolution Japanese ALOS PALSAR sensor were evaluated for suitability in vernal pool detection beneath forest canopies. In a two phase study, potential vernal pool (PVP) detection was first assessed with unsupervised PALSAR (LHH) two season change detection (spring when flooded—summer when dry) and validated with 268, 1 ha field-sampled test cells. This resulted in low false negatives (14%–22%), overall map accuracy of 48% to 62% and high commission error (66%). These results make this blind two-season PALSAR approach for cryptic PVP detection of use for locating areas of high vernal pool likelihood. In a second phase of the research, PALSAR was integrated with 10 m USGS DEM derivatives in a machine learning classifier, which greatly improved overall PVP map accuracies (91% to 93%). This supervised approach with PALSAR was found to produce better mapping results than using LiDAR intensity or C-band SAR data in a fusion with the USGS DEM-derivatives

Assessing Boreal Peat Fire Severity and Vulnerability of Peatlands to Early Season Wildland Fire

Globally peatlands store large amounts of carbon belowground with 80% distributed in boreal regions of the northern hemisphere. Climate warming and drying of the boreal region has been documented as affecting fire regimes, with increased fire frequency, severity and extent. While much research is dedicated to assessing changes in boreal uplands, few research efforts are focused on the vulnerability of boreal peatlands to wildfire. In this case study, an integration of field data collection, land cover mapping of peatland types and Landsat-based fire severity mapping was conducted for four early season (May to mid-June) wildfires where peatlands are abundant in northeastern Alberta Canada. The goal was to better understand if peatlands burn more or less preferentially than uplands in fires and how severely the organic soil layers (peat) of different peatland ecotypes burn. The focus was on early season wildfires because they dominated the research area in the decade of study. To do this, a novel Landsat-5 metric was developed to retrieve fire severity of the organic surface layer. Spatial comparisons and statistical analysis showed that proportionally bogs are more likely to burn in early season Alberta wildfires than other ecosystem types, even fire-prone upland conifer. Although for a small sample, we found that when fire weather conditions for the duff layers are severe, the fens of this study appear to become more susceptible to burning. In addition, overall bogs experienced greater severity of burn to the peat layers than fens. Due to the small sample size of peat loss from fire in uplands and limited geographic area of this case study, we were unable to assess if bogs are burning more severely than uplands. Further analysis and Landsat algorithm development for organic soil fire severity in peatlands and uplands are needed to more fully understand trends in belowground consumption for wildfires of all seasons and boreal ecotypes

Mapping mountain peatlands and wet meadows using multi-date, multi-sensor remote sensing in the Cordillera Blanca, Peru

Wetlands (called bofedales in the Andes of Peru) are abundant and important components of many mountain ecosystems across the globe. They provide many benefits including water storage, high quality habitat, pasture, nutrient sinks and transformations, and carbon storage. The remote and rugged setting of mountain wetlands creates challenges for mapping, typically leading to misclassification and underestimates of wetland extent. We used multi-date, multi-sensor radar and optical imagery (Landsat TM/PALSAR/RADARSAT-1/SRTM DEM-TPI) combined with ground truthing for mapping wetlands in Huascarán National Park, Peru. We mapped bofedales into major wetland types: 1) cushion plant peatlands, 2) cushion plant wet meadows, and 3) graminoid wet meadows with an overall accuracy of 92%. A fourth wetland type was found (graminoid peatlands) but was too rare to map accurately, thus it was combined with cushion peatland to form a single peatland class. Total wetland area mapped in the National Park is 38,444 ha, which is 11% of the park area. Peatlands were the most abundant wetland type occupying 6.3% of the park, followed by graminoid wet meadows (3.5%) and cushion wet meadows (1.3%). These maps will serve as the foundation for improved management, including restoration, and estimates of landscape carbon stocks

Development of a bi-national Great Lakes coastal wetland and land use map using three-season PALSAR and landsat imagery

Methods using extensive field data and three-season Landsat TM and PALSAR imagery were developed to map wetland type and identify potential wetland stressors (i.e., adjacent land use) for the United States and Canadian Laurentian coastal Great Lakes. The mapped area included the coastline to 10 km inland to capture the region hydrologically connected to the Great Lakes. Maps were developed in cooperation with the overarching Great Lakes Consortium plan to provide a comprehensive regional baseline map suitable for coastal wetland assessment and management by agencies at the local, tribal, state, and federal levels. The goal was to provide not only land use and land cover (LULC) baseline data at moderate spatial resolution (20–30 m), but a repeatable methodology to monitor change into the future. The prime focus was on mapping wetland ecosystem types, such as emergent wetland and forested wetland, as well as to delineate wetland monocultures (Typha, Phragmites, Schoenoplectus) and differentiate peatlands (fens and bogs) from other wetland types. The overall accuracy for the coastal Great Lakes map of all five lake basins was 94%, with a range of 86% to 96% by individual lake basin (Huron, Ontario, Michigan, Erie and Superior)

Bottom-Up Drivers of Future Fire Regimes in Western Boreal North America

Forest characteristics, structure, and dynamics within the North American boreal region are heavily influenced by wildfire intensity, severity, and frequency. Increasing temperatures are likely to result in drier conditions and longer fire seasons, potentially leading to more intense and frequent fires. However, an increase in deciduous forest cover is also predicted across the region, potentially decreasing flammability. In this study, we use an individual tree-based forest model to test bottom-up (i.e. fuels) vs top-down (i.e. climate) controls on fire activity and project future forest and wildfire dynamics. The University of Virginia Forest Model Enhanced is an individual tree-based forest model that has been successfully updated and validated within the North American boreal zone. We updated the model to better characterize fire ignition and behavior in relation to litter and fire weather conditions, allowing for further interactions between vegetation, soils, fire, and climate. Model output following updates showed good agreement with combustion observations at individual sites within boreal Alaska and western Canada. We then applied the updated model at sites within interior Alaska and the Northwest Territories to simulate wildfire and forest response to climate change under moderate (RCP 4.5) and extreme (RCP 8.5) scenarios. Results suggest that changing climate will act to decrease biomass and increase deciduous fraction in many regions of boreal North America. These changes are accompanied by decreases in fire probability and average fire intensity, despite fuel drying, indicating a negative feedback of fuel loading on wildfire. These simulations demonstrate the importance of dynamic fuels and dynamic vegetation in predicting future forest and wildfire conditions. The vegetation and wildfire changes predicted here have implications for large-scale changes in vegetation composition, biomass, and wildfire severity across boreal North America, potentially resulting in further feedbacks to regional and even global climate and carbon cycling

Patterns of Ecosystem Structure and Wildfire Carbon Combustion Across Six Ecoregions of the North American Boreal Forest

Increases in fire frequency, extent, and severity are expected to strongly impact the structure and function of boreal forest ecosystems. An important function of the boreal forest is its ability to sequester and store carbon (C). Increasing disturbance from wildfires, emitting large amounts of C to the atmosphere, may create a positive feedback to climate warming. Variation in ecosystem structure and function throughout the boreal forest is important for predicting the effects of climate warming and changing fire regimes on C dynamics. In this study, we compiled data on soil characteristics, stand structure, pre-fire C pools, C loss from fire, and the potential drivers of these C metrics from 527 sites distributed across six ecoregions of North America’s western boreal forests. We assessed structural and functional differences between these fire-prone ecoregions using data from 417 recently burned sites (2004–2015) and estimated ecoregion-specific relationships between soil characteristics and depth from 167 of these sites plus an additional 110 sites (27 burned, 83 unburned). We found that northern boreal ecoregions were generally older, stored and emitted proportionally more belowground than aboveground C, and exhibited lower rates of C accumulation over time than southern ecoregions. We present ecoregion-specific estimates of depth-wise soil characteristics that are important for predicting C combustion from fire. As climate continues to warm and disturbance from wildfires increases, the C dynamics of these fire-prone ecoregions are likely to change with significant implications for the global C cycle and its feedbacks to climate change

A review of carbon monitoring in wet carbon systems using remote sensing

Carbon monitoring is critical for the reporting and verification of carbon stocks and change. Remote sensing is a tool increasingly used to estimate the spatial heterogeneity, extent and change of carbon stocks within and across various systems. We designate the use of the term wet carbon system to the interconnected wetlands, ocean, river and streams, lakes and ponds, and permafrost, which are carbon-dense and vital conduits for carbon throughout the terrestrial and aquatic sections of the carbon cycle. We reviewed wet carbon monitoring studies that utilize earth observation to improve our knowledge of data gaps, methods, and future research recommendations. To achieve this, we conducted a systematic review collecting 1622 references and screening them with a combination of text matching and a panel of three experts. The search found 496 references, with an additional 78 references added by experts. Our study found considerable variability of the utilization of remote sensing and global wet carbon monitoring progress across the nine systems analyzed. The review highlighted that remote sensing is routinely used to globally map carbon in mangroves and oceans, whereas seagrass, terrestrial wetlands, tidal marshes, rivers, and permafrost would benefit from more accurate and comprehensive global maps of extent. We identified three critical gaps and twelve recommendations to continue progressing wet carbon systems and increase cross system scientific inquiry

Andes, Bofedales, and the Communities of Huascarán National Park, Peru

Universidad Nacional Agraria La Molina. Escuela de Posgrado. Maestría en Producción AnimalMountain wetlands are abundant in the high elevations of the tropical Andes. Wetlands occupy ~11% of the total park area and are mostly found in the large mountain valleys. Wetlands occur up to 5000 m asl, but most occur between 4,000–4,700 m asl. The highest elevation wetlands are typically dominated by cushion plants, while lower elevation wetlands are more commonly occupied by graminoids. About 60% of all wetlands are peatlands and the remainder are mineral soil wet meadows. The peatlands are up to 11 m deep and 12,000 years old, storing an average of 2,101 Mg C ha-1, which is comparable to lowland tropical peatlands. Our work in Huascarán National Park in Peru is also showing the importance of wetlands in a coupled natural-human system. These wetlands and alpine landscapes are shaped in part by legacies of past human land use, including ancient pastoralism and farming, and are also affected by millions of downstream users dependent upon wetlands and glacier-fed streams for water and energy production. Biodiversity and endemism is high among taxonomic groups such as plants, birds, fish, amphibians and insects. Currently the tropical Andes are in ecological flux due to rapid land cover changes caused by both biophysical and socioeconomic drivers. In addition, the high Andes are experiencing warming and rapid glacial retreat that is resulting in hydroecological changes and socioeconomic changes to the traditional Andean societies that feed back to changes in wetland sustainability

Increasing fire and the decline of fire adapted black spruce in the boreal forest

Intensifying wildfire activity and climate change can drive rapid forest compositional shifts. In boreal North America, black spruce shapes forest flammability and depends on fire for regeneration. This relationship has helped black spruce maintain its dominance through much of the Holocene. However, with climate change and more frequent and severe fires, shifts away from black spruce dominance to broadleaf or pine species are emerging, with implications for ecosystem functions including carbon sequestration, water and energy fluxes, and wildlife habitat. Here, we predict that such reductions in black spruce after fire may already be widespread given current trends in climate and fire. To test this, we synthesize data from 1,538 field sites across boreal North America to evaluate compositional changes in tree species following 58 recent fires (1989 to 2014). While black spruce was resilient following most fires (62%), loss of resilience was common, and spruce regeneration failed completely in 18% of 1,140 black spruce sites. In contrast, postfire regeneration never failed in forests dominated by jack pine, which also possesses an aerial seed bank, or broad-leaved trees. More complete combustion of the soil organic layer, which often occurs in better-drained landscape positions and in dryer duff, promoted compositional changes throughout boreal North America. Forests in western North America, however, were more vulnerable to change due to greater long-term climate moisture deficits. While we find considerable remaining resilience in black spruce forests, predicted increases in climate moisture deficits and fire activity will erode this resilience, pushing the system toward a tipping point that has not been crossed in several thousand years