Geology ReportsSearch

USGS · 70208398

Multi-decadal patterns of vegetation succession after tundra fire on the Yukon-Kuskokwim Delta, Alaska

Abstract

Alaska’s Yukon-Kuskokwim Delta (YKD) is one of the warmest parts of the Arctic tundra biome and tundra fires are common in its upland areas. Here we combine field measurements, Landsat observations, and quantitative cover maps for tundra plant functional types (PFTs) to characterize multi-decadal succession and landscape change after fire in lichen-dominated upland tundra of the YKD, where extensive wildfires occurred in 1971–1972, 1985, 2006–2007, and 2015. Unburned tundra was characterized by abundant lichens and low lichen cover was consistently associated with historical fire. While we observed some successional patterns that were consistent with earlier work in Alaskan tussock tundra, other patterns were not. In the landscape we studied, a large proportion of pre-fire moss cover and surface peat tended to survive fire, which favors survival of existing vascular plants and limits opportunities for seed recruitment. Although shrub cover was much higher in 1985 and 1971–1972 burns than in unburned tundra, tall shrubs (>0.5 m height) were rare and the PFT maps indicate high landscape-scale variability in the degree and persistence of shrub increase after fire. Fire has induced persistent changes in species composition and structure of upland tundra on the YKD, but the lichen-dominated fuels and thick surface peat appear to have limited the potential for severe fire and accompanying edaphic changes. Soil thaw depths were about 10 cm deeper in 2006–2007 burns than in unburned tundra, but were similar to unburned tundra in 1985 and 1971–1972 burns. Historically, repeat fire has been rare on the YKD, and the functional diversity of vegetation has recovered within several decades post-fire. Our findings provide a basis for predicting and monitoring post-fire tundra succession on the YKD and elsewhere.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 58.619777025081675° to 63.30281270313518° latitude; -167.958984375° to -157.52197265625° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Gerald Frost, Rachel A. Loehman, Lisa Saperstein, Matthew J. Macander, Peter Nelson, David Paradis, Sue M. Natali. 2020-01-30. Multi-decadal patterns of vegetation succession after tundra fire on the Yukon-Kuskokwim Delta, Alaska. https://doi.org/10.1088/1748-9326%2Fab5f49

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Characterizing operational signatures of reservoirs with the SWOT satellite by comparing natural lake and reservoir dynamics

Due to a lack of management operations data, hydrological models may represent reservoirs as natural lakes, leading to poor discharge predictions in regulated basins. To parse seasonal operational signatures, we compare the dynamics of natural lake and reservoir systems across North America using Surface Water and Ocean Topography (SWOT) satellite observations and derived discharge estimates. Overall, reservoirs and their adjacent river reaches exhibit significantly greater variability (in standard deviation) than their natural counterparts across almost all SWOT observed (e.g. water surface elevation) and inferred (e.g. discharge) variables. Natural lakes show strong same-day correlations between inflow and outflow discharge (median Spearman R = 0.8), whereas 76% of reservoirs exhibit maximum correlation when outflow is lagged, suggesting operations buffer seasonal flow variability. Our findings indicate operations not only affect reservoir dynamics themselves but also have upstream and downstream consequences, which, when integrated into models, will offer more realistic hydrologic conditions.

Environmental Research Letters

Compounding of 100-year coastal floods by rainfall in an urban environment

Coastal and pluvial flooding are both becoming more prevalent and severe due to climate change and urbanization in floodplains. The co-occurrence of these flood drivers is generally assumed to exacerbate the resulting flood impacts, a result referred to as compound flooding. However, few observational or modeling studies have investigated the circumstances under which this occurs. Here, we study the impacts of these combined flood drivers and evaluate the implicit hypothesis of official flood maps, which is that rainfall has a negligible impact on the flood depth and flooded area due to a 100 year coastal flood. A coastal system model, configured to capture coastal and pluvial flood drivers, is used. We evaluate the flooding for different urban landform types, including coastal landfill (human-made land), convergent areas (topographic depressions) and other urban terrain, within a model domain covering the Jamaica Bay watershed of New York City. A scenario-based strategy is adopted with a 100 year coastal flood as a control simulation, to which we add a set of realistic scenarios of rainfall data from historical tropical cyclones. We also apply a joint probability analysis framework with historical data to evaluate the probability of these compound coastal-pluvial scenarios. Results reveal cases where the pluvial driver compounds the coastal flood through expansion of the flood zone, with a 17% chance of rainfall increasing the flood area by 6%–38%, and a 5% chance of an increase of 61%–73%. It is rare that floods are significantly deepened but when deepening occurs, it is more common for the convergent zone than for the coastal landfill. These findings quantitatively assess the potential of the pluvial driver to exacerbate flooding, which may influence emergency management strategies such as evacuation plans, shelter arrangements, and related preparedness measures.

New York

Estimates of global surface water dynamics harnessing near real-time land cover observations and open science geospatial capabilities

Spatio-temporal changes to our world’s surface water resources are escalating. Translating how these changes impact communities and ecosystems requires time-varying data of Global Surface Water Extents (GSWE). Traditionally, GSWE mapping has been limited to static estimates, with recent efforts focusing on annual averages, frequency and occurrence of long-term variations. Building upon these foundational capabilities, we harnessed remotely sensed Sentinel-2 based near real-time Dynamic World (DW) land cover products to produce the first-of-its-kind 10 m resolution GSWE dataset representing 2015–2023. Our dataset estimated 2.5 million km 2 of permanent waters and 8 million km 2 of seasonal waters worldwide. Comparing our Sentinel-2 based data to contemporary Landsat-based GSWE, we observed that our data mapped less water within the >50% probability of occurrence range, suggesting a lower presence of open permanent water especially in high latitudes, deviating from what we previously learnt from Landsat data. Statistical analysis compared to well-established observational products and widely used GSWE datasets across some of the world’s most ecologically significant regions, including Pantanal in South America and Haor in South Asia, supports the overall physical realism of our data in predicting global open surface water dynamics. Our key contribution is a prototype Open Science operational framework that extracts routinely available DW products, runs geospatial analytics, and creates actionable water information for educators, researchers, and stakeholders at any scale of practical interest. We present examples of this operational capability through instant mapping of flood in Spain and drought in Lake Urmia, Central Asia, frequent monitoring of river extent changes at the Ganges–Brahmaputra confluence, and above all, interoperability with other existing GSWE applications.

Environmental Research Letters