Upscaling methane emission hotspots in boreal peatlands

Upscaling the properties and the effects of small-scale surface heterogeneities to larger scales is a challenging issue in land surface modeling. We developed a novel approach to upscale local methane emissions in a boreal peatland from the micro-topographic scale to the landscape-scale. We based this new parameterization on the analysis of the water table pattern generated by the Hummock–Hollow model, a micro-topography resolving model for peatland hydrology. We introduce this parameterization of methane hotspots in a global model-like version of the Hummock–Hollow model, that underestimates methane emissions. We tested the robustness of the parameterization by simulating methane emissions for the next century forcing the model with three different RCP scenarios. The Hotspot parameterization, despite being calibrated for the 1976–2005 climatology, mimics the output of the micro-topography resolving model for all the simulated scenarios. The new approach bridges the scale gap of methane emissions between this version of the model and the configuration explicitly resolving micro-topography

PeRL : a circum-Arctic Permafrost Region Pond and Lake database

Ponds and lakes are abundant in Arctic permafrost lowlands. They play an important role in Arctic wetland ecosystems by regulating carbon, water, and energy fluxes and providing freshwater habitats. However, ponds, i. e., waterbodies with surface areas smaller than 1.0 x 10(4) m(2), have not been inventoried on global and regional scales. The Permafrost Region Pond and Lake (PeRL) database presents the results of a circum-Arctic effort to map ponds and lakes from modern (2002-2013) high-resolution aerial and satellite imagery with a resolution of 5m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6m or better. PeRL includes 69 maps covering a wide range of environmental conditions from tundra to boreal regions and from continuous to discontinuous permafrost zones. Waterbody maps are linked to regional permafrost landscape maps which provide information on permafrost extent, ground ice volume, geology, and lithology. This paper describes waterbody classification and accuracy, and presents statistics of waterbody distribution for each site. Maps of permafrost landscapes in Alaska, Canada, and Russia are used to extrapolate waterbody statistics from the site level to regional landscape units. PeRL presents pond and lake estimates for a total area of 1.4 x 10(6) km(2) across the Arctic, about 17% of the Arctic lowland (Peer reviewe

Probabilistic downscaling of remote sensing data with applications for multi-scale biogeochemical flux modeling

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes

Northern Eurasia Future Initiative (NEFI): facing the challenges and pathways of global change in the 21st century

During the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies co-designed with regional decision makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include: warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land-use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia's role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large scale water withdrawals, land use and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that Integrated Assessment Models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts

A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams

Subgrid processes occur in various ecosystems and landscapes but, because of their small scale, they are not represented or poorly parameterized in climate models. These local heterogeneities are often important or even fundamental for energy and carbon balances. This is especially true for northern peatlands and in particular for the polygonal tundra, where methane emissions are strongly influenced by spatial soil heterogeneities.We present a stochastic model for the surface topography of polygonal tundra using Poisson– Voronoi diagrams and we compare the results with available recent field studies. We analyze seasonal dynamics of water table variations and the landscape response under different scenarios of precipitation income. We upscale methane fluxes by using a simple idealized model for methane emission. Hydraulic interconnectivities and large-scale drainage may also be investigated through percolation properties and thresholds in the Voronoi graph. The model captures the main statistical characteristics of the landscape topography, such as polygon area and surface properties as well as the water balance. This approach enables us to statistically relate large-scale properties of the system to the main small-scale processes within the single polygons

Modeling micro-topographic controls on boreal peatland hydrology and methane fluxes

Small-scale surface heterogeneities can influence land–atmosphere fluxes and therefore carbon, water and energy budgets on larger scale. This effect is of particular relevance for high-latitude ecosystems, because of the great amount of carbon stored in their soils. We introduce a novel micro-topographic model, the Hummock–Hollow (HH) model, which explicitly represents small-scale surface elevation changes. By computing the water table at the small scale, and by coupling the model with a process-based model for soil methane processes, we are able to model effects of micro-topography on hydrology and methane emissions in a typical boreal peatland. In order to assess the effect of micro-topography on water balance and methane emissions of the peatland we compare two versions of the model, one with a representation of micro-topography and a classical single-bucket model version, and show that the temporal variability in the model version with micro-topography performs better if compared with local data. Accounting for micro-topography almost triples the cumulative methane flux over the simulated time-slice. We found that the single-bucket model underestimates methane emissions because of its poor performance in representing hydrological dynamics. The HH model with micro-topography captures the spatial dynamics of water and methane fluxes, being able to identify the hotspots for methane emissions. The model also identifies a critical scale (0.01 km2) which marks the minimal resolution for the explicit representation of micro-topography in larger-scale models

Modeling micro-topographic controls on boreal peatland hydrology and methane fluxes

Small-scale surface heterogeneities can influence land-atmosphere fluxes and therefore carbon, water and energy budgets on a larger scale. This effect is of particular relevance for high-latitude ecosystems, because of the great amount of carbon stored in their soils. We introduce a novel micro-topographic model, the Hummock-Hollow (HH) model, which explicitly represents small-scale surface elevation changes. By computing the water table at the small scale, and by coupling the model with a process-based model for soil methane processes, we are able to model the effects of micro-topography on hydrology and methane emissions in a typical boreal peatland. In order to assess the effect of micro-topography on water the balance and methane emissions of the peatland we compare two versions of the model, one with a representation of micro-topography and a classical single-bucket model version, and show that the temporal variability in the model version with micro-topography performs better if compared with local data. Accounting for micro-topography almost triples the cumulative methane flux over the simulated time-slice. We found that the single-bucket model underestimates methane emissions because of its poor performance in representing hydrological dynamics. The HH model with micro-topography captures the spatial dynamics of water and methane fluxes, being able to identify the hotspots for methane emissions. The model also identifies a critical scale (0.01 km2) which marks the minimal resolution for the explicit representation of micro-topography in larger-scale models. © 2015 Author(s)