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These data contain measurements from a four-component net radiometer, as well as 2-m temperature, pressure, and relative humidity. In addition, soil moisture and temperature measurements and soil heat fluxes are included.
ABSTRACT Climate change is causing an increase in drought in many soil ecosystems and a loss of soil organic carbon. Calcareous soils may partially mitigate these losses via carbon capture and storage. Here, we aimed to determine how irrigation-supplied soil moisture and perennial plants impact biotic and abiotic soil properties that underpin deep soil carbon chemistry in an unfertilized calcareous soil. Soil was sampled up to 1 m in depth from irrigated and planted field treatments and was analyzed using a suite of omics and chemical analyses. The soil microbial community composition was impacted more by irrigation and plant cover treatments than by soil depth. By contrast, metabolomes, lipidomes, and proteomes differed more with soil depth than treatments. Deep soil (>50 cm) had higher soil pH and calcium concentrations and higher levels of organic acids, bicarbonate, and triacylglycerides. By contrast, surface soil (0–5 cm) had higher concentrations of soil organic matter, organic carbon, oxidizable carbon, and total nitrogen. Surface soils also had higher amounts of sugars, sugar alcohols, phosphocholines, and proteins that reflect osmotic and oxidative stress responses. The lipidome was more responsive to perennial tall wheatgrass treatments compared to the metabolome or proteome, with a striking change in diacylglyceride composition. Permanganate oxidizable carbon was more consistently correlated to metabolites and proteins than soil organic and inorganic carbon and soil organic matter. This study reveals specific compounds that reflect differences in organic, inorganic, and oxidizable soil carbon fractions that are impacted by interactions between irrigation-supplied moisture and plant cover in calcareous soil profiles. IMPORTANCE Carbon is cycled through the air, plants, and belowground environment. Understanding soil carbon cycling in deep soil profiles will be important to mitigate climate change. Soil carbon cycling is impacted by water, plants, and soil microorganisms, in addition to soil mineralogy. Measuring biotic and abiotic soil properties provides a perspective of how soil microorganisms interact with the surrounding chemical environment. This study emphasizes the importance of considering biotic interactions with inorganic and oxidizable soil carbon in addition to total organic carbon in carbonate-containing soils for better informing soil carbon management decisions.
Warm-season rainfall associated with mesoscale convective systems (MCSs) in the central US is characterized by higher intensity and nocturnal timing compared to rainfall from non-MCS systems, suggesting their potentially different footprints on the land surface. To differentiate the impacts of MCS and non-MCS rainfall on the surface water balance, a water tracer tool embedded in the Noah land surface model with multi-parameterization options (WT-Noah-MP) is used to numerically “tag” water from MCS and non-MCS rainfall separately during April to August (1997-2018) and track their transit in the terrestrial system. From the water-tagging results, over 50% of warm-season rainfall leaves the surface-subsurface system through evapotranspiration by the end of August, but non-MCS rainfall contributes a larger fraction. However, MCS rainfall plays a more important role in generating surface runoff. These differences are mostly attributed to the rainfall intensity differences. The higher intensity MCS rainfall tends to produce more surface runoff through infiltration excess flow and drives a deeper penetration of the rainwater into the soil. Over 70% of the top 10 percentile runoff is contributed by MCS rainfall, demonstrating its important contribution to local flooding. In contrast, lighter intensity non-MCS rainfall resides mostly in the top layer and contributes more to evapotranspiration through soil evaporation. Diurnal timing of rainfall has negligible effects on the flux partitioning for both MCS and non-MCS rainfall. Differences in soil moisture profiles for MCS and non-MCS rainfall and the resultant evapotranspiration suggest differences in their roles in soil moisture-precipitation feedbacks and ecohydrology.
Hydrologic variability is a serious threat to the poverty-stricken regions of North Africa. Meanwhile, the scientific community struggles to attribute these extreme climatic episodes to specific oceanic and land drivers. Prior modeling studies have not assessed simulated feedbacks over North Africa against an established observational benchmark, so their results are considered as untested, model-specific findings. The Coupled Model Intercomparison Project Phase Five (CMIP5) archive represents the state-of-the-art in climate projections, with most CMIP5 models now containing interactive vegetation phenology; however, there have been no studies to date of their simulated vegetation feedbacks. The capability of CMIP5 models at accurately simulating the forcing of both sea-surface temperature (SST) and regional leaf area index (LAI) anomalies on North African climate needs to be a key consideration in assessing the models’ overall credibility and determining appropriate model weighting for developing climate projections. The Generalized Equilibrium Feedback Assessment (GEFA) is a promising statistical method, which can be applied to either model output or observations, for isolating the local and remote impacts of individual oceanic or terrestrial forcings on regional climate. We performed a combined observational and modeling assessment of land-ocean-atmosphere interactions across the distinct ecological and moisture gradients of North Africa. We evaluated and demonstrated the reliability of the GEFA statistical method over North Africa using the Community Earth System Model (CESM), applied GEFA to observational data to quantify the observed forcing of ocean basin SST anomalies and regional LAI anomalies on North African climate, evaluated the CMIP5 models’ performance in terms of representing these key observed feedbacks, and formulated CMIP5 feedback performance metrics for weighting North African climate projections. Our study represented the first attempt to separate the observed roles of oceanic and vegetation feedbacks across North Africa, the first systematic assessment and intercomparison of land-ocean-atmosphere feedbacks in CMIP5, and the first exploration of vegetation feedbacks among CMIP5 models. The following work was accomplished. (1) The team generated 14 scientific publications and 30 presentations based on the DOE-funded research. (2) A stepwise version of the GEFA statistical method was developed in which unimportant forcings were dropped to increase the reliability of the results. (3) SGEFA was successfully validated through experiments with CESM in terms of its ability to isolate the atmospheric responses to individual oceanic or land forcings. (4) Observational evidence was revealed for the Sahel’s positive vegetation-rainfall feedback on the seasonal to interannual time scale, and it was attributed to a moisture recycling mechanism rather than an albedo mechanism. (5) An approach with SGEFA was developed in which the individual contributions of soil moisture versus vegetation forcings could be separated, revealing that the former forcing outweighed the latter for sub-Saharan Africa. (6) Tropical ocean temperatures were found to be key regulators of pan-tropical vegetation variability, especially for arid and semi-arid regions, including sub-Saharan Africa. (7) The CMIP5 models largely underestimated the importance of land feedbacks across the Sahel. (8) The general consensus among CMIP5 models indicates, for the late 21st century, a diminished seasonal predictability of sub-Saharan African regional climate and an elevated role of the land surface compared to oceanic drivers in regulating regional climate variability. (9) Land-ocean-atmosphere interactions were demonstrated to be key contributors to the seasonal predictability of African wildfire activity. (10) The El Djouf was determined to be of greater importance than the Bodélé depression in terms of providing trans-Atlantic dust transport to the Americas.
This dataset contains Electromagnetic Induction (EMI) data collected at Trail Creek, Colorado, in 2024. EMI surveys were conducted to investigate the spatial distribution of electrical conductivity in the subsurface, providing insights into soil moisture and subsurface geological features. The surveys were performed along multiple transects to capture variations in conductivity influenced by changes in soil composition, moisture content, and underlying geological structures. This dataset complements other geophysical data collected in the region, including Electrical Resistivity Tomography (ERT) and Terrestrial LiDAR Scanning (TLS), providing a detailed understanding of the subsurface and its impact on surface vegetation and hydrological processes. The data are valuable for environmental geophysics, ecological research, and hydrological modeling in mountainous ecosystems. The files include: - data.zip: the raw EMI data (.csv) - inversion.zip: the inverted resistivity model (.csv and .kml) - kriging.zip: the kriging resistivity model (.csv, .tif, .kmz) - flmd.csv: file level metadata file describing all files within this dataset - dd.csv: data dictionary file describing the column headers within CSV files This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.
Anoxic microsites, zones of oxygen depletion in otherwise oxic soils, may slow soil C turnover. However, the abundance of anoxic microsites and their contribution to soil C protection is yet undefined. In this study, we determine the contribution of anoxic microsites to soil C protection in soils of three distinct textures (clay loam, loam, sandy loam) across a range of soil moistures. We examined the influence of soil oxygen supply by increasing oxygen content in the incubation atmosphere (oxygen enrichment) and through disaggregation. We attributed increases in CO 2 efflux to the aeration of anoxic microsites. The contribution of anoxic microsites to soil C protection increased with decreasing clay content. Clay loam CO 2 efflux was relatively unaffected by aeration. Moderately moist, loam soils had CO 2 effluxes that did not increase with oxygen enrichment but increased by 375% upon disaggregation. Sandy loam soil CO 2 efflux increased by 50–75% with oxygen enrichment and 250% with disaggregation. Geochemical and microbial data reveal that anoxic microsite abundance also increased with decreasing clay content. The proportion of acid extractable Fe present as Fe(II) increased with decreasing clay content, and methanogens were more abundant in loam and sandy loam soils. Our results suggest that oxygen demand, rather than supply, can regulate anoxic microsite formation and that anoxic protection of soil C can be diminished through physical disruption of soil structure. Our findings further illustrate that anoxic microsites should be included in conceptual models of soil C protection to avoid soil C loss and improve predictions of soil C response to disturbance.
Abstract In tropical forests, both vegetation characteristics and soil properties are important not only for controlling energy, water, and gas exchanges directly but also determining the competition among species, successional dynamics, forest structure and composition. However, the joint effects of the two factors have received limited attention in Earth system model development. Here we use a vegetation demographic model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM), ELM‐FATES, to explore how plant traits and soil properties affect tropical forest growth and composition concurrently. A large ensemble of simulations with perturbed vegetation and soil hydrological parameters is conducted at the Barro Colorado Island, Panama. The simulations are compared against observed carbon, energy, and water fluxes. We find that soil hydrological parameters, particularly the scaling exponent of the soil retention curve ( B sw ), play crucial roles in controlling forest diversity, with higher B sw values (>7) favoring late successional species in competition, and lower B sw values (1 ∼ 7) promoting the coexistence of early and late successional plants. Considering the additional impact of soil properties resolves a systematic bias of FATES in simulating sensible/latent heat partitioning with repercussion on water budget and plant coexistence. A greater fraction of deeper tree roots can help maintain the dry‐season soil moisture and plant gas exchange. As soil properties are as important as vegetation parameters in predicting tropical forest dynamics, more efforts are needed to improve parameterizations of soil functions and belowground processes and their interactions with aboveground vegetation dynamics.
Land-atmosphere feedbacks are a critical component of the hydrologic cycle. Vertical profiles of boundary layer temperature and moisture, together with information about the land surface, are used to compute land-atmosphere coupling metrics. Ground based remote sensing platforms, such as the Atmospheric Emitted Radiance Interferometer (AERI), can provide high temporal resolution vertical profiles of temperature and moisture. When co-located with soil moisture, surface flux, and surface meteorological observations, such as at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, it is possible to observe both the terrestrial and atmospheric legs of land-atmosphere feedbacks. In this study, we compare a commonly used coupling metric computed from radiosonde-based data to that obtained from the AERI to characterize the accuracy and uncertainty in the metric derived from the two distinct platforms. This approach demonstrates the AERI’s utility where radiosonde observations are absent in time and/or space. Radiosonde and AERI based observations of the Convective Triggering Potential and Low-Level Humidity Index (CTP-HI low ) were computed during the 1200 UTC observation time and displayed good agreement during both 2017 and 2019 warm seasons. Furthermore, radiosonde and AERI derived metrics diagnosed the same atmospheric preconditioning based upon the CTP-HI low framework a majority of the time. When retrieval uncertainty was considered, even greater agreement was found between radiosonde and AERI derived classification. The AERI’s ability to represent this coupling metric well enabled novel exploration of temporal variability within the overnight period in CTP and HI low . Observations of CTP-HI low computed within a few hours of 1200 UTC were essentially equivalent, however with greater differences in time arose greater differences in CTP and HI low .
This study evaluates how environmental parameters that integrate biogeochemical processes vary with water table fluctuations in the freshwater Wax Lake Delta (WLD) in Louisiana, U.S.A. This data package contains seven *.csv files and one Excel file that compiles all the data from the individual .csv files. This dataset reports high frequency (15-min) observations of water level, soil redox potential, specific conductance, and pH made for one year along elevation transects located on the older, proximal (OT) and younger, distal (YT) ends of a deltaic island. Water depth relative to the ground surface (cm; HOBO U20L-04; error ± 0.4 cm), water pH and temperature (HOBO MX2501), and specific conductance and temperature (HOBO U24-001) sensors were installed in March 2023. Water depth was corrected for barometric pressure recorded by a separate logger secured to a platform above the highest water level. Soil redox probes (SWAP ORP-40-4-B) were also installed in March 2023. Each probe had four Pt sensors (2 mm width) placed at 10 cm, 20 cm, 30 cm, and 40 cm below the ground surface. Redox data were referenced to an external Ag0/AgCl (3M KCl) reference probe placed in saturated ground and recorded on CR1000X dataloggers (Campbell Scientific) powered by solar panels. A second reference probe was positioned near the primary reference probe for backup and data correction. The tops of the soil redox probes and soil moisture probes were flush with the soil surface so that sensors are reported at their indicated depths below ground surface. Here, we report data collected between 15 March 2023 to 15 March 2024 for all sensors, with some differences due to exact dates of sensor placement or data gaps associated with sensor malfunction. For example, water depth at OT4 was not recorded between March to November 2023. Data flags indicate whether a value is valid (1) or was excluded from data analysis in the associated manuscript (-1).
Establish publicly available open-source, high-resolution datasets of greenhouse gas (GHG) emissions, meteorology, soil, and vegetation to support testing and validation of emerging biofuel production monitoring technologies. The project team deployed latest technologies to collect “Gold Standard” data for field- level fluxes of CO 2 , N 2 O, CH 4 and H 2 O in grain sorghum production systems in Texas, Oklahoma, and Kansas. The Oklahoma State University led SMARTFARM was initiated on Oct 1, 2020, due to COVID-19 pandemic delay. We installed closed-path dual laser Eddy Covariance (EC) flux measurement system along with a well-established open-path EC system for simultaneously measuring field-level fluxes of CO 2 , N 2 O, CH 4 , and H2O. The eddy flux data are combined with sub-acre soil moisture and temperature measurements, plant and soil analysis data (nutrient, composition, carbon, growth, and phenology), spatial surveys of soil EC, and pH. Grain sorghum crop was managed including planting and harvesting by producers. All teams recruited postdocs and students for the project and submitted purchase orders for field equipment. The team has developed a draft impact sheet and finalized the advisory board for the project.
The Baltimore Turfgrass Field Experiment (BTFE) consisted of an observation eddy covariance flux station, measuring CO 2 , H 2 O, and turbulent energy fluxes between the turfgrass field and the atmosphere. The tower was sited before the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s arrival, but for the purposes of this report, we can say that the campaign lasted as long as the Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) campaign, 12 months, 12/2024 through 11/2025. As stated, the flux tower was part of the COURAGE campaign on the M1 site. We set out to measure turfgrass because it is a ubiquitous part of the urban environment—in fact, it is the dominant vegetation land cover type in Baltimore and most cities. It contributes small but significantly to greenhouse gas balances as well as the energy balance in the urban environment. We also installed a soil temperature and matric potential profiling system as part of this experiment. Additionally, AmeriFlux asked us to participate in their soil matric potential soil moisture mapping experiment. We collected 12 soil samples to be analyzed by a team in Bloomington, Indiana: results are pending.
The Baltimore Ecosystem Study (BES) established a network of long-term permanent biogeochemical study plots in 1998. These plots provide long-term data on vegetation, soil and hydrologic processes in the key ecosystem types within the urban ecosystem. The network of study plots includes forest plots (upland and riparian), chosen to represent the range of forest conditions in the area and grass plots (to represent home lawns). Plots are instrumented with lysimeters (drainage and tension) to sample soil solution chemistry, time domain reflectometry probes to measure soil moisture, dataloggers to measure and record soil temperature, and trace gas flux chambers to measure the flux of carbon dioxide, nitrous oxide and methane from soil to the atmosphere. Measurements of in situ nitrogen mineralization, nitrification and denitrification were made at approximately monthly intervals from Fall 1998 - Fall 2000. Detailed vegetation characterization (all layers) was done in summer 1998 and 2015. Data from these plots has been published in Groffman et al. (2006, 2009), Groffman and Pouyat (2009), Savva et al. (2010), Costa and Groffman (2013), Duncan et al. (2013), Waters et al. (2014), Ni and Groffman (2018), Templeton et al. (2019). Literature Cited Costa, K.H. and P.M. Groffman. 2013. Factors regulating net methane flux in urban forests and grasslands. Soil Science Society of America Journal 77:850 - 855. Duncan, J. M., L. E. Band, and P. M. Groffman. 2013. Towards closing the watershed nitrogen budget: Spatial and temporal scaling of denitrification. Journal of Geophysical Research Biogeosciences 118:1-5; DOI: 10.1002/jgrg.20090 Groffman PM, Pouyat RV, Cadenasso ML, Zipperer WC, Szlavecz K, Yesilonis IC,. Band LE and Brush GS. 2006. Land use context and natural soil controls on plant community composition and soil nitrogen and carbon dynamics in urban and rural forests. Forest Ecology and Management 236:177-192. Groffman, P.M., C.O. Williams, R.V. Pouyat, L.E. Band and I.C. Yesilonis. 2009. Nitrate leaching and nitrous oxide flux in urban forests and grasslands. Journal of Environmental Quality 38:1848-1860. Groffman, P.M. and R.V. Pouyat. 2009. Methane uptake in urban forests and lawns. Environmental Science and Technology 43:5229-5235. DOI: 10.1021/es803720h. Ni, X. and P.M. Groffman. 2018. Declines in methane uptake in forest soils. Proceedings of the National Academies of Science of the United States of America 115:8587-8590. Savva, Y., K. Szlavecz, R. V. Pouyat, P. M. Groffman, and G. Heisler. 2010. Effects of land use and vegetation cover on soil temperature in an urban ecosystem. Soil Science Society of America Journal 74:469-480. Templeton, L., M.L. Cadenasso, J. Sullivan, M. Neel and P.M. Groffman. 2019. Changes in vegetation structure and composition of urban and rural forest patches in Baltimore from 1998 to 2015. Forest Ecology and Management. In press. Waters, E.R., J.L. Morse, N.D. Bettez and P.M. Groffman. 2014. Differential carbon and nitrogen controls of denitrification in riparian zones and streams along an urban to exurban gradient. Journal of Environmental Quality 43:955–963.
We present observations from a laboratory-controlled study on the impacts of extreme wetting and drying on a wetland soil microbiome. Our approach was to experimentally challenge the soil microbiome to understand impacts on anaerobic carbon cycling processes as the system transitions from dryness to saturation and vice-versa. Specifically, we tested for impacts on stress responses related to shifts from wet to drought conditions. We used a combination of high-resolution data for small organic chemical compounds (metabolites) and biological (community structure based on 16S rRNA gene sequencing) features. Using a robust correlation-independent data approach, we further tested the predictive power of soil metabolites for the presence or absence of taxa. Here, we demonstrate that taking an untargeted, multidimensional data approach to the interpretation of metabolomics has the potential to indicate the causative pathways selecting for the observed bacterial community structure in soils.
The K34 tower site (2.609 S, 60.209 W, 130 masl), located within the Tropical Silviculture Experimental Station (EEST, also known as ZF2) research station, in an area of undisturbed tropical forest (Araújo et al. 2002). It features long term measurements using micrometeorological, eddy covariance, and soil instrumentation, among others. This dataset covers January 2012 to December 2017, and includes air temperature (TA, ℃) and air relative humidity (RH, %), measured with thermohygrometers (HC2S3, Campbell Scientific, Logan, UT, USA) deployed above the canopy at the top of the tower (at 51.1 m height), and net radiation (NETRAD, W m-2) using an NR-LITE sensor (Kipp & Zonen, Delft, Netherlands), also at the top of the tower (at 35.0 m above the canopy). The soil moisture data included here is from a soil profile located approximately 12 m from the tower, and covers the period between February 2015 and September 2016. Volumetric soil water content (SWC, m3 m-3) measurements used Water Content Reflectometers (CS655 Campbell Scientific, Logan, UT, USA) at six depths: 10 cm, 20 cm, 30 cm, 40 cm, 60 cm, and 100 cm. Data are included in .csv files, and the text file ZF2-K34_Tower_headers.txt provides descriptions of data file headers.
Climate-driven permafrost thaw alters the strongly coupled carbon and nitrogen cycles within the Arctic tundra, influencing the availability of limiting nutrients including nitrate (NO3−). Researchers have identified two primary mechanisms that increase nitrogen and NO3− availability within permafrost soils: (1) the ‘frozen feast’, where previously frozen organic material becomes available as it thaws, and (2) ‘shrubification’, where expansion of nitrogen-fixing shrubs promotes increased soil nitrogen. Through the synthesis of original and previously published observational data, and the application of multiple geospatial approaches, this study investigates and highlights a third mechanism that increases NO3− availability: the hydrogeomorphic evolution of polygonal permafrost landscapes. Permafrost thaw drives changes in microtopography, increasing the drainage of topographic highs, thus increasing oxic conditions that promote NO3− production and accumulation. We extrapolate relationships between NO3− and soil moisture in elevated topographic features within our study area and the broader Alaskan Coastal Plain and investigate potential changes in NO3− availability in response to possible hydrogeomorphic evolution scenarios of permafrost landscapes. These approximations indicate that such changes could increase Arctic tundra NO3− availability by ~250–1000%. Thus, hydrogeomorphic changes that accompany continued permafrost degradation in polygonal permafrost landscapes will substantially increase soil pore water NO3− availability and boost future fertilization and productivity in the Arctic.
The purpose of this study was to evaluate the effect of Timber Mountain recharge on groundwater flow in the surrounding Pahute Mesa-Oasis Valley groundwater basin using several different methodologies. These methodologies included examining climatic and soil moisture data, estimating groundwater recharge by chloride mass balance, interpreting water chemical and isotopic data, and modeling groundwater flow along faults.
Daily averages of soil temperature and moisture measured once every hour at different heights, as well as daily averages of hourly measured snow depths located at Intensive Monitoring Stations at Council Road Mile Marker 71 site. Deployed at each site is an Onset HOBO U30 data logger with five smart temperature sensors and three smart soil moisture sensors (10HS). Three sites (CN_IS_4, CN_IS_6A, CN_IS_7) are equipped with a snow depth sensor. Data are retrieved annually since 2016. Contains 53 *.CSV files including a file inventory list by year. Data files have header rows, NaN fields indicate invalid or missing data, and negative vertical offsets are above ground. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
Transpiration is a globally important component of evapotranspiration. Careful upscaling of transpiration from point measurements is thus crucial for quantifying water and energy fluxes. In spatially heterogeneous landscapes common across the boreal biome, upscaled transpiration estimates are difficult to determine due to variation in local environmental conditions (e.g., basal area, soil moisture, permafrost). Here, we sought to determine stand-level attributes that influence transpiration scalars for a forested boreal peatland complex consisting of sparsely treed wetlands and densely treed permafrost plateaus as land cover types. The objectives were to quantify spatial and temporal variability in stand-level transpiration, and to identify sources of uncertainty when scaling point measurements to the stand-level. Using heat ratio method sap flow sensors, we determined sap velocity for black spruce and tamarack for 2-week periods during peak growing season in 2013, 2017 and 2018. We found greater basal area, drier soils, and the presence of permafrost increased daily sap velocity in individual trees, suggesting that local environmental conditions are important in dictating sap velocity. When sap velocity was scaled to stand-level transpiration using gridded 20 × 20 m resolution data across the ~10 ha Scotty Creek ForestGEO plot, we observed significant differences in daily plot transpiration among years (0.17–0.30 mm), and across land cover types. Daily transpiration was lowest in grid-cells with sparsely treed wetlands compared to grid-cells with well-drained and densely treed permafrost plateaus, where daily transpiration reached 0.80 mm, or 30% of the daily evapotranspiration. When transpiration scalars (i.e., sap velocity) were not specific to the different land cover types (i.e., permafrost plateaus and wetlands), scaled stand-level transpiration was overestimated by 42%. To quantify the relative contribution of tree transpiration to ecosystem evapotranspiration, we recommend that sampling designs stratify across local environmental conditions to accurately represent variation associated with land cover types, especially with different hydrological functioning as encountered in rapidly thawing boreal peatland complexes.