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This is the AmeriFlux version of the carbon flux data for the site US-PFs SE5 Aspen-5 CHEESEHEAD 2019. Site Description - This tower (12m Rohn) is located in the southeastern quadrant of the 10 x 10km study domain. It is located in an aspen regrowth forest (canopy height: 3.1 - 6 m).
This is the AmeriFlux version of the carbon flux data for the site US-PFt SE6 Pine-4 CHEESEHEAD 2019. Site Description - This tower (32m, trailer-based, telescoping) is located in the southeastern quadrant of the 10 x 10km study domain. It is located in a red pine forest (canopy height: 15 - 21.6 m).
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFb NW1 Pine-1 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFb NW1 Pine-1 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is the northwestern most tower in the 10 x 10km study domain. It is located in a red pine forest (canopy height ~25m). There is a regrowing/trap layer consisting of broadleaf aspen and other deciduous vegetation.
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFk SW1 Aspen-2 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFk SW1 Aspen-2 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is located in the southwestern quadrant of the 10 x 10km study domain. It is located in an aspen forest (canopy height: immediate vicinity - 10m; greater area - 24.4 m).
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFL SW2 Aspen-3 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFL SW2 Aspen-3 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (25m Rohn) is located in the southwestern quadrant of the 10 x 10km study domain. It is located in an aspen forest (canopy height: 15 - 19.2 m).
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFm SW3 Hardwood-2 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFm SW3 Hardwood-2 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is located in the southwestern quadrant of the 10 x 10km study domain. It is located in an aspen and maple forest (canopy height: 15 m).
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFq SE3 Aspen-4 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFq SE3 Aspen-4 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is located in the southeastern quadrant of the 10 x 10km study domain. It is located in an aspen forest (canopy height: 10 - 14.3 m).
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFt SE6 Pine-4 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFt SE6 Pine-4 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is located in the southeastern quadrant of the 10 x 10km study domain. It is located in a red pine forest (canopy height: 15 - 21.6 m).
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFi NE3 Hardwood-1 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFi NE3 Hardwood-1 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is located in the northeastern quadrant of the 10 x 10km study domain. It is located in a mixed hardwood forest (canopy height: 18 - 20m).
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFj NE4 Maple-1 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFj NE4 Maple-1 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is located in the northeastern quadrant of the 10 x 10km study domain. It is located in a maple forest (canopy height: 18 - 20m). Some conifers mixed in, more conifers to the NNW.
Rapid wide-area assessments of vegetation encroachment on transmission and distribution line rights-of-way (ROW) is a highly desirable capability for understanding risks to the power grid during severe weather and wildfire events. Conventional assessments are time-consuming and expensive due to the need for in-situ inspections and the use of aerial assets. Performing conventional assessments on a wide area would require immense resources and time that might not be available within the horizon of an expected adverse event. Developing a capability to accurately assess vegetation encroachment into ROWs will enable faster analysis of potential grid vulnerabilities in NAERM. This project sought to develop a prototype capability for rapid ROW vegetation encroachment assessments by using Puerto Rico as a test case. Puerto Rico is a heavily forested island territory frequently impacted by tropical cyclones that threaten the electric grid by downing trees across transmission and distribution lines. Multispectral satellite imagery (MSI) enable very high resolution (i.e., 0.5 - 2 meter) assessment of vegetation conditions at scale and with revisit times appropriate for regular monitoring (e.g., weekly to quarterly, depending on cloud cover) of the entire island. Synthetic aperture radar (SAR) data from satellites was also investigated as solution to the cloud-cover issue as they are active sensors that emit and receive a microwave signal rather than relying on solar illumination, and are therefore unaffected by cloud cover and can collect data during day or night. Finally, MSI-derived digital surface models (DSMs) map the height of objects relative to sea level, and were assessed for their ability to estimate the height of forest canopies relative to coincident transmission lines. The results of the mapping investigation are described in this report.
This dataset contains data from a manipulative field study aimed at identifying critical thresholds for acute response of plants and ecosystems to water stress (TARP) that took place at Walker Branch Watershed in Oak Ridge, Tennessee from 2002-2005 (2002-06-20 to 2005-12-16). The study used understory tents for the removal of 100% of the growing-season throughfall and stem flow, to provide data on the impact of acute drought on mechanisms responsible for growth and mortality of deciduous forest canopy trees representative of common plant functional types (Liriodendron and Quercus). Through three years of manipulation (2003, 2004 and 2005; pretreatment measurements in 2002) various measures of tree response to surface moisture deficits were recorded including root and leaf traits, plant nonstructural carbohydrates status, hourly sapflow, basal area, and periodic observations of foliar photosynthesis and conductance. Additionally, environmental data such as air and soil temperature, soil water content, and soil matric potential were recorded. This dataset contains data 16 files in comma-separate (*.csv) format. Additional metadata are provided: 16 data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.
Abstract. In this study, the Noah land surface model used in conjunction with the Mellor–Yamada–Janjić surface layer scheme (hereafter, Noah-MYJ) and the Noah multiphysics scheme (Noah-MP) from the Weather Research and Forecasting (WRF) 4.5.1 mesoscale model are evaluated with regard to their performance in reproducing positive temperature gradients over forested areas in the Arctic winter. First, simplified versions of the WRF schemes, recoded in Python, are compared with conceptual models of the surface layer in order to gain insight into the dependence of the temperature gradient on the wind speed at the top of the surface layer. It is shown that the WRF schemes place strong limits on the turbulent collapse, leading to lower surface temperature gradient at low wind speeds than in the conceptual models. We implemented modifications to the WRF schemes to correct this effect. The original and modified versions of Noah-MYJ and Noah-MP are then evaluated compared to long-term measurements at the Ameriflux Poker Flat Research Range, a forest site in interior Alaska. Noah-MP is found to perform better than Noah-MYJ because the former is a two-layer model which explicitly takes into account the effect of the forest canopy. Indeed, a non-negligible temperature gradient is maintained below the canopy at high wind speeds, leading to overall larger gradients than in the absence of vegetation. Furthermore, the modified versions are found to perform better than the original versions of each scheme because they better reproduce strong temperature gradients at low wind speeds.
Tree growth and survival differ strongly between canopy trees (those directly exposed to overhead light), and understory trees. However, the structural complexity of many tropical forests makes it difficult to determine canopy positions. The integration of remote sensing and ground-based data enables this determination and measurements of how canopy and understory trees differ in structure and dynamics. Here we analyzed 2 cm resolution RGB imagery collected by a Remotely Piloted Aircraft System (RPAS), also known as drone, together with two decades of bi-annual tree censuses for 2 ha of old growth forest in the Central Amazon. We delineated all crowns visible in the imagery and linked each crown to a tagged stem through field work. Canopy trees constituted 40% of the 1244 inventoried trees with diameter at breast height (DBH) > 10 cm, and accounted for ~70% of aboveground carbon stocks and wood productivity. The probability of being in the canopy increased logistically with tree diameter, passing through 50% at 23.5 cm DBH. Diameter growth was on average twice as large in canopy trees as in understory trees. Growth rates were unrelated to diameter in canopy trees and positively related to diameter in understory trees, consistent with the idea that light availability increases with diameter in the understory but not the canopy. The whole stand size distribution was best fit by a Weibull distribution, whereas the separate size distributions of understory trees or canopy trees > 25 cm DBH were equally well fit by exponential and Weibull distributions, consistent with mechanistic forest models. The identification and field mapping of crowns seen in a high resolution orthomosaic revealed new patterns in the structure and dynamics of trees of canopy vs. understory at this site, demonstrating the value of traditional tree censuses with drone remote sensing.
Accurate understanding of the variability in foliar physiological traits across landscapes is critical to improve parameterization and evaluation of terrestrial biosphere models (TBMs) that seek to represent the response of terrestrial ecosystems to a changing climate. Numerous studies suggest imaging spectroscopy can characterize foliar biochemical and morphological traits at the canopy scale, but there is only limited evidence for retrieving canopy photosynthetic capacity (e.g., maximum carboxylation rate, V c,max and maximum electron transport rate, J max ). Moreover, the effect of canopy structure within forest communities on scaling up spectra-trait relationships from leaf to canopy level is not well known. To advance the spectra-trait approach and enable the estimation of key traits using remote sensing, we collected imaging spectroscopy data from an Unoccupied Aerial System (UAS) platform over two forest sites in China (a subtropical forest in Mt. Dinghu and a tropical rainforest in Xishuangbanna). At these sites, we also collected ground measurements of leaf spectra and traits, including biochemical (leaf nitrogen, phosphorus, chlorophyll, and water content), morphological (leaf mass per area, LMA) and physiological (V c,max25 and J max25 ) traits (n=135 tree-crowns from 42 species across two sites). Using a partial least-squares regression (PLSR) approach, we built and tested spectra-trait models with repeated cross-validation. The spectral models developed with leaf spectra were directly transferred to canopy spectra to evaluate the effect of canopy structure. Here we further applied canopy spectral models to map these traits at individual tree-crown scale. The results demonstrate that (1) UAS-based canopy spectra can be used to estimate V c,max (R 2 =0.55, nRMSE=11.79%), Jmax (R 2 =0.54, nRMSE=12.34%), and five additional foliar traits (R 2 =0.38-0.60, nRMSE=10.11-13.56%) at the tree-crown scale with demonstrated generalizability across two sites; (2) canopy structure strongly affects the spectratrait relationships from leaf to canopy level, but the effects vary considerably across foliar traits and cannot be well captured by the 4SAIL canopy radiative transfer model. UAS-based imaging spectroscopy maps large variability in all foliar traits (including physiological traits) with spatially explicit information, reproducing the field-observed inter- and intra-specific variations. These results demonstrate the capability of using UAS-based imaging spectroscopy for characterizing the variability of foliar physiological traits at individual tree-crown scale over forest landscapes and highlight the similar generalizability but different biophysical mechanisms underlying spectra-trait relationships at leaf and canopy levels.
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-MtB Mt Bigelow. This is the FLUXNET version of the carbon flux data for the site US-MtB Mt Bigelow produced by applying the standard ONEFlux (1F) software. Site Description - Western slope of Mt. Bigelow; 29 km NE of Tucson, AZ, USA; Mixed evergreen conifer forest; Average canopy height = 10 m; Summer monsoon; 30-m tower installed in 2002; Secondary forest re-established in the 1930s
Vegetation parameters for the Variable Infiltration Capacity (VIC) hydrologic model were recently updated using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS). Previous work showed that these MODIS-based parameters improved VIC evapotranspiration simulations when compared to eddy covariance observations. Due to the importance of evapotranspiration within the Colorado River basin, this study provided a basin-by-basin calibration of VIC soil parameters with updated MODIS-based vegetation parameters to improve streamflow simulations. Interestingly, while both configurations had similar historic streamflow performance, end-of-century hydrologic projections, driven by 29 downscaled global climate models under the RCP8.5 emissions scenario, differed between the two configurations. The calibrated MODIS-based configuration had an ensemble mean that simulated little change in end-of-century annual streamflow volume (+0.4%) at Lees Ferry, Arizona, relative to the historical period (1960–2005). In contrast, the previous VIC configuration, which is used to inform decisions about future water resources in the Colorado River basin, projected an 11.7% decrease in annual streamflow. Both VIC configurations simulated similar amounts of evapotranspiration in the historical period. However, the MODIS-based VIC configuration did not show as much of an increase in evapotranspiration by the end of the century, primarily within the upper basin’s forested areas. Differences in evapotranspiration projections were the result of the MODIS-based vegetation parameters having lower leaf area index values and less forested area compared to previous vegetation estimates used in recent Colorado River basin hydrologic projections. These results highlight the need to accurately characterize vegetation and better constrain climate sensitivities in hydrologic models.
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