Research Assistant Professor Alaska Coastal Rainforest Center

Recent Submissions

  • Big avalanches in a changing climate: Using tree-ring Derived avalanche chronologies to examine avalanche frequency across multiple climate types

    Peitzsch, Erich H.; Pederson, Gregory; Martin, Justin; Hood, Eran; Greene, Ethan; Birkeland, Kelly Elder; Wolken, Gabriel; Kichas, Nick; Stahle, Daniel; Harley, John R. (Montana State University Library, 2023-10-08)
    Large-magnitude snow avalanches pose a hazard to humans and infrastructure worldwide. Analyzing the spatiotemporal behavior of avalanches and the contributory climate factors is important for understanding historical variability in climate-avalanche relationships as well as improving avalanche forecasting. This study uses established dendrochronological methods to develop long-term regional avalanche chronologies for three different climate types: high-latitude maritime climate of southeast Alaska, intermountain climate of the northern Rocky Mountains, and continental climate of Colorado. In the maritime study area, we collected 434 cross sections throughout six avalanche paths near Juneau, Alaska. This resulted in 2706 identified avalanche growth disturbances between year 1720 and 2018 Common Era (CE), which allowed us to reconstruct 82 years with large magnitude avalanche activity across three sub-regions. By combining this tree-ring derived avalanche dataset with a suite of climate and atmospheric variables and applying a generalized linear model to fit a binomial regression, we found February and March precipitation and the Oceanic Niño Index (ONI) were significant predictors of large magnitude avalanche activity in the southeast Alaska study area. In the intermountain climate study area, tree-rings from 647 trees exhibited 2134 avalanche-related growth disturbances in the northern Rocky Mountains of northwest Montana from 1867 to 2019. The data show that the amount of snowpack across the northern Rocky Mountain region is directly related to avalanche probability. Coincident with warming and regional snowpack reductions, a decline of ~ 14% (~ 2% per decade) in overall large magnitude avalanche probability is apparent through the period 1950–2017 CE. In the continental climate of Colorado, we sampled 24 avalanche paths throughout the state and collected 1188 total samples with 4135 identified growth disturbances from 1698 to 2019. Preliminary results suggest years with large magnitude avalanche activity across the sub-regions of this study area are generally characterized by stormy winters with above average snowpack development but that early and late winter temperature and precipitation also play an important role in large avalanche activity. Characterizing historical climate-avalanche relationships across different climate types provides a broad baseline for understanding potential future changes in avalanche activity. Overall, this work helps forecasters and planners better understand the influence of climate on large magnitude avalanche frequency, and how potential changes in avalanche character and occurrence will affect their operations in the context of a warming climate.
  • Riverine dissolved inorganic carbon export from the Southeast Alaskan Drainage Basin with implications for coastal ocean processes

    Harley, John R.; Biles, Frances E.; Brooks, Mariela K.; Fellman, Jason M.; Hood, Eran; D'Amore, David V. (American Geophysical Union, 2023-10-16)
    Dissolved inorganic carbon (DIC) represents an important but poorly constrained form of lateral carbon flux to the oceans. With high precipitation rates, large glaciers, and dense temperate rainforest, Southeast Alaska plays a critical role in the transport of carbon to the Gulf of Alaska (GOA). Previous estimates of DIC flux across the Southeast Alaska Drainage Basin (SEAKDB) are poorly constrained in space and time. Our goal was to incorporate recent measurements of DIC concentrations with previous measurements from the U.S. Geological Survey in order to model the spatial and temporal patterns of riverine DIC transport from SEAK to the GOA. We aggregated DIC concentration measurements from 1957 to 2020 and associated measurements of mean daily discharge. We then constructed load estimation models to generate concentration predictions across 24 watersheds. By spatially matching measurements of DIC with SEAKDB watersheds, we extrapolated concentration predictions across 2,455 watersheds encompassing approximately 190,000 km2. Models were aggregated according to two factors, the presence of karst and the discharge regime. Finally, monthly flux predictions were generated for each watershed using predicted concentrations and runoff estimates from the Distributed Climate Water Balance Model. Mean annual DIC flux from the SEAKDB was 2.36 Tg C with an average yield of 12.52 g C m−2. Both karst presence and flow regimes modified DIC flux and speciation across coastal marine areas. The high resolution of DIC flux estimates will provide useful inputs for describing seasonal C dynamics, and further refines our understanding of C budgets in the Pacific temperate rainforest and the surrounding marine environment.
  • Tree-ring derived avalanche frequency and climate associations in a high-latitude, maritime climate

    Peitzsch, Erich H.; Hood, Eran; Harley, John R.; Stahle, D. K.; Kichas, Nickolas E.; Wolken, Gabriel (American Geophysical Union, 2023-07-28)
    Snow avalanches are a natural hazard in mountainous areas worldwide with severe impacts that include fatalities, damage to infrastructure, disruption to commerce, and landscape disturbance. Understanding long-term avalanche frequency patterns, and associated climate and weather influences, improves our understanding of how climate change may affect avalanche activity. We used dendrochronological techniques to evaluate the historical frequency of large magnitude avalanches (LMAs) in the high-latitude climate of southeast Alaska, United States. We collected 434 cross sections throughout six avalanche paths near Juneau, Alaska. This resulted in 2706 identified avalanche growth disturbances between 1720 and 2018, which allowed us to reconstruct 82 years with LMA activity across three sub-regions. By combining this tree-ring-derived avalanche data set with a suite of climate and atmospheric variables and applying a generalized linear model to fit a binomial regression, we found that February and March precipitation and the Oceanic Niño Index (ONI) were significant predictors of LMA activity in the study area. Specifically, LMA activity occurred during winters with substantial February and March precipitation and neutral or negative (cold) ONI values, while years not characterized by LMAs occur more frequently during warm winters (positive ONI values). Our examination of the climate-avalanche relationship in southeast Alaska sheds light on important climate variables and physical processes associated with LMA years. These results can be used to inform long-term infrastructure planning and avalanche mitigation operations in an urban area, such as Juneau, where critical infrastructure is subject to substantial avalanche hazard.
  • The Southeast Alaska Tribal Ocean Research (SEATOR) Partnership: Addressing Data Gaps in Harmful Algal Bloom Monitoring and Shellfish Safety in Southeast Alaska

    Harley, John Robinson; Lanphier, Kari; Kennedy, Esther G.; Leighfield, Tod A.; Bidlack, Allison Lynn; Gribble, Matthew O.; Whitehead, Christopher (MDPI, 2020-06-19)
    Many communities in Southeast Alaska harvest shellfish such as mussels and clams as an important part of a subsistence or traditional diet. Harmful algal blooms (HABs) of phytoplankton such as Alexandrium spp. produce toxins that can accumulate in shellfish tissues to concentrations that can pose a hazard for human health. Since 2013, several tribal governments and communities have pooled resources to form the Southeast Alaska Tribal Ocean Research (SEATOR) network, with the goal of minimizing risks to seafood harvest and enhancing food security. SEATOR monitors toxin concentrations in shellfish and collects and consolidates data on environmental variables that may be important predictors of toxin levels such as sea surface temperature and salinity. Data from SEATOR are publicly available and are encouraged to be used for the development and testing of predictive algorithms that could improve seafood risk assessment in Southeast Alaska. To date, more than 1700 shellfish samples have been analyzed for paralytic shellfish toxins (PSTs) in more than 20 locations, with potentially lethal concentrations observed in blue mussels (Mytilus trossulus) and butter clams (Saxidomus gigantea). Concentrations of PSTs exhibit seasonality in some species, and observations of Alexandrium are correlated to sea surface temperature and salinity; however, concentrations above the threshold of concern have been found in all months, and substantial variation in concentrations of PSTs remain unexplained.