Search for: All records

The decision to establish a network of researchers centers on identifying shared research goals. Ecologically specific regions, such as the USA’s National Ecological Observatory Network’s (NEON’s) eco-climatic domains, are ideal locations by which to assemble researchers with a diverse range of expertise but focused on the same set of ecological challenges. The recently established Great Lakes User Group (GLUG) is NEON’s first domain specific ensemble of researchers, whose goal is to address scientific and technical issues specific to the Great Lakes Domain 5 (D05) by using NEON data to enable advancement of ecosystem science. Here, we report on GLUG’s kick off workshop, which comprised lightning talks, keynote presentations, breakout brainstorming sessions and field site visits. Together, these activities created an environment to foster and strengthen GLUG and NEON user engagement. The tangible outcomes of the workshop exceeded initial expectations and include plans for (i) two journal articles (in addition to this one), (ii) two potential funding proposals, (iii) an assignable assets request and (iv) development of classroom activities using NEON datasets. The success of this 2.5-day event was due to a combination of factors, including establishment of clear objectives, adopting engaging activities and providing opportunities for active participation and inclusive collaboration with diverse participants. Given the success of this approach we encourage others, wanting to organize similar groups of researchers, to adopt the workshop framework presented here which will strengthen existing collaborations and foster new ones, together with raising greater awareness and promotion of use of NEON datasets. Establishing domain specific user groups will help bridge the scale gap between site level data collection and addressing regional and larger ecological challenges.

 

Structurally complex forests optimize resources to assimilate carbon more effectively, leading to higher productivity. Information obtained from Light Detection and Ranging (LiDAR)‐derived canopy structural complexity (CSC) metrics across spatial scales serves as a powerful indicator of ecosystem‐scale functions such as gross primary productivity (GPP). However, our understanding of mechanistic links between forest structure and function, and the impact of disturbance on the relationship, is limited. Here, we paired eddy covariance measurements of carbon and water fluxes from nine forested sites within the 10 × 10 km CHEESEHEAD19 study domain in Northern Wisconsin, USA with drone LiDAR measurements of CSC to establish which CSC metrics were strong drivers of GPP, and tested potential mediators of the relationship. Mechanistic relationships were inspected at five resolutions (0.25, 2, 10, 25, and 50 m) to determine whether relationships persisted with scale. Vertical heterogeneity metrics were the most influential in predicting productivity for forests with a significant degree of heterogeneity in management, forest type, and species composition. CSC metrics included in the structure‐function relationship as well as driver strength was dependent on metric calculation resolution. The relationship was mediated by light use efficiency (LUE) and water use efficiency (WUE), with WUE being a stronger mediator and driver of GPP. These findings allow us to improve representation in ecosystem models of how CSC impacts light and water‐sensitive processes, and ultimately GPP. Improved models enhance our capacity to accurately simulate forest responses to management, furthering our ability to assess climate mitigation strategies.

 

Abstract. This study investigates and compares soil moisture andhydrology projections of broadly used land models with permafrost processesand highlights the causes and impacts of permafrost zone soil moistureprojections. Climate models project warmer temperatures and increases inprecipitation (P) which will intensify evapotranspiration (ET) and runoff inland models. However, this study shows that most models project a long-termdrying of the surface soil (0–20 cm) for the permafrost region despiteincreases in the net air–surface water flux (P-ET). Drying is generallyexplained by infiltration of moisture to deeper soil layers as the activelayer deepens or permafrost thaws completely. Although most models agree ondrying, the projections vary strongly in magnitude and spatial pattern.Land models tend to agree with decadal runoff trends but underestimaterunoff volume when compared to gauge data across the major Arctic riverbasins, potentially indicating model structural limitations. Coordinatedefforts to address the ongoing challenges presented in this study will helpreduce uncertainty in our capability to predict the future Arctichydrological state and associated land–atmosphere biogeochemical processesacross spatial and temporal scales. 

The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model–data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon–Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world’s highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models. 

High‐latitude climate change has impacted vegetation productivity, composition, and distribution across tundra ecosystems. Over the past few decades in northern Alaska, emergent macrophytes have increased in cover and density, coincident with increased air and water temperature, active layer depth, and nutrient availability. Unraveling the covarying climate and environmental controls influencing long‐term change trajectories is paramount for advancing our predictive understanding of the causes and consequences of warming in permafrost ecosystems. Within a climate‐controlled carbon flux monitoring system, we evaluate the impact of elevated nutrient availability associated with degraded permafrost (high‐treatment) and maximum field observations (low‐treatment), on aquatic macrophyte growth and methane (CH₄) emissions. Nine aquaticArctophila fulva‐dominated tundra monoliths were extracted from tundra ponds near Utqiaġvik, Alaska, and placed in growth chambers that controlled ambient conditions (i.e., light, temperature, and water table), while measuring plant growth (periodically) and CH₄fluxes (continuously) for 12 weeks. Results indicate that high nutrient treatments similar to that released from permafrost thaw can increase macrophyte biomass and total CH₄emission by 54 and 64%, respectively. However, low treatments did not respond to fertilization. We estimate that permafrost thaw in tundra wetlands near Utqiaġvik have the potential to enhance regional CH₄efflux by 30%. This study demonstrates the sensitivity of arctic tundra wetland biogeochemistry to nutrient release from permafrost thaw and suggests the decadal‐scale expansion ofA. fulva‐dominant aquatic plant communities, and increased CH₄emissions in the region were likely in response to thawing permafrost, potentially representing a novel case study of the permafrost carbon feedback to warming.

 

Plant‐mediatedCH₄flux is an important pathway for land–atmosphereCH₄emissions, but the magnitude, timing, and environmental controls, spanning scales of space and time, remain poorly understood in arctic tundra wetlands, particularly under the long‐term effects of climate change.CH₄fluxes were measuredin situduring peak growing season for the dominant aquatic emergent plants in the Alaskan arctic coastal plain,Carex aquatilisandArctophila fulva, to assess the magnitude and species‐specific controls onCH₄flux. Plant biomass was a strong predictor ofA. fulvaCH₄flux while water depth and thaw depth were copredictors forC. aquatilisCH₄flux. We used plant and environmental data from 1971 to 1972 from the historic International Biological Program (IBP) research site near Barrow, Alaska, which we resampled in 2010–2013, to quantify changes in plant biomass and thaw depth, and used these to estimate species‐specific decadal‐scale changes inCH₄fluxes. A ~60% increase inCH₄flux was estimated from the observed plant biomass and thaw depth increases in tundra ponds over the past 40 years. Despite covering only ~5% of the landscape, we estimate that aquaticC. aquatilisandA. fulvaaccount for two‐thirds of the total regionalCH₄flux of the Barrow Peninsula. The regionally observed increases in plant biomass and active layer thickening over the past 40 years not only have major implications for energy and water balance, but also have significantly altered land–atmosphereCH₄emissions for this region, potentially acting as a positive feedback to climate warming.