Disentangling tree and shrub phenology in Siberian taiga ecosystems; National Geographic, Committee on Research and Exploration, 2016-2017
In forests throughout the northern hemisphere the timing of leaf emergence in the spring and leaf senescence in the fall, referred to as canopy phenology, has been changing in response to global climate. Canopy phenology is important because it corresponds to growing season length, which in turn strongly influences how vegetation impacts global climate via affects on atmospheric carbon, water, and energy dynamics. In dense forests with continuous tree cover satellites can be used to monitor canopy phenology, but in open forests with low tree density it may be difficult to determine whether there are differences in phenology between trees or understory shrubs. Yet in open forests these differences between will be important for understanding ecosystem responses and feedbacks to continued climate change. Therefore, near surface monitoring techniques such as repeat digital photography will be imperative for understanding phenological change in these ecosystems. The purpose of this study is to quantify differences in canopy phenology for trees and shrubs in low-density boreal larch forests in far northeastern Siberia using near surface optical measurements. These deciduous conifer forests cover over 3-million km2, have low canopy density, and a deciduous broadleaf shrub understory. Optical measurements from this study will be combined with ecosystem level vegetation inventories for stands with differing densities and mutli-scale satellite images leveraged from other studies to disentangle the effects of trees and shrubs on canopy phenology. Results will improve understanding of how Siberian larch forests will respond and feedback to global climate.
Impacts of boreal climate feedbacks on climate change; Picker Interdisciplinary Science Institute, Colgate University, 2016-2018
Pronounced climate warming at high latitudes in the northern hemisphere is reducing the duration and spatial extent of seasonal snow cover. This reduction in snow cover leads to increased absorption of solar radiation at the earth surface because snow has high albedo, or reflectivity, in comparison to vegetation. This increase in absorbed radiation leads to further warming, which in turn further reduces snow cover extent, constituting a positive feedback cycle referred to as the Snow Albedo Feedback (SAF).
Climate model representations of the SAF vary widely in relation to empirical estimates derived using satellite observations and reanalysis data products. This spread in model representations of SAF was present in the Coupled Model Intercomparison Project Phase 3 (CMIP3, which informed the Intergovernmental Panel on Climate Change’s Fourth Assessment Report), and it persisted through the Coupled Model Intercomparison Project Phase 5 (CMIP5, which informed the Intergovernmental Panel on Climate Change’s Fifth Assessment Report). This spread in SAF strength among models effectively introduces uncertainty in model projections of future climatic change, particularly as it relates to boreal regions. Several analyses have indicated that model representation of boreal forests and associated energy dynamics are likely responsible for variability between models, especially as it relates to the inability of models to reproduce recent observed changes in snow cover extent.
The most recent IPCC Assessment Report has identified this as a pressing issue that urgently needs to be addressed. Here we propose to combine the expertise of ecologists, snow hydrologists, and climate modelers to improve process understanding and model representation of boreal forest-snow interactions. We will accomplish this using a hierarchical combination of field observations, geospatial data products, and climate model outputs. Our research will leverage data from previous projects as well as several current funding sources that will significantly enhance the value and impact of the project. The results will provide useful benchmarks and process representations of boreal forest-snow processes that will be useful in upcoming international climate model experiments.
Vegetation and ecosystem impacts on permafrost vulnerability; NSF Arctic System Science 2015 – 2018
Realistic representations of heat exchange in permafrost ecosystems are necessary for accurate predictive understanding of the permafrost carbon feedback under future climate scenarios. This project will provide a quantitative pan-arctic assessment of the effects of vegetation and landscape characteristics on permafrost thermal regimes. By working across ecosystems, landscape characteristics, and regions, the research will identify broad trends, and intensive energy balance sites will provide a mechanistic study of ecosystem impacts on permafrost response to climate change. The impacts of this study will be enhanced through integration of research results into regional and site-specific permafrost models and synthesis activities that will examine ecosystem impacts on energy balance and permafrost vulnerability to climate change.
Fire regime influences on carbon dynamics of Siberian boreal forests; NSF Arctic System Science, 2013 – 2017
Boreal forests cover 40% of the vegetated land area above the Arctic Circle and are a critical component of arctic ecosystems. Global change models predict boreal forests will become increasingly susceptible to fire activity with climate warming. Because these forests contain a large proportion of global terrestrial carbon (C) stocks, changes in the fire regime are likely to alter global C cycling. Increased fire activity will increase C emissions to the atmosphere, with a potential positive feedback to climate warming. However, an altered fire regime may also initiate cascading effects on forest regrowth and permafrost degradation that could magnify or offset this feedback. Fire effects on these ecological mechanisms remain uncertain but will ultimately determine whether arctic ecosystems act as a C source or sink under future climate change scenarios. The primary objective of this research is to increase our understanding of post-fire C dynamics in boreal forests of the Siberian arctic by elucidating the ecological mechanisms by which increased fire severity could influence C accumulation and storage over the successional interval. The overarching hypothesis is that post-fire soil organic layer (SOL) depth regulates net ecosystem carbon balance (NECB) through indirect impacts on forest regrowth and permafrost stability because of its role as a barrier to seed germination and thermal regulator. The team will: 1) link near term fire effects on SOL depth to changes in larch recruitment and permafrost characteristics in experimental burn plots created in 2012, 2) determine the relationship between post-fire stand structure and above- and belowground C pools at the local and landscape level across stands of varying age and topographic positions, and 3) test via experimental manipulations and field observations the mechanisms by which fire-driven changes in stand density indirectly affect moss growth, SOL development, and susceptibility of deeper C pools to warming, decomposition, and release into the atmosphere. This research will offer novel insights into the importance of both vegetation and soil processes within arctic ecosystems in determining the net feedback of an intensified fire regime to the climate system.