Detailed assessment of small‐scale heterogeneity in local surface water balance is essential to accurate estimation of evapotranspiration in semiarid climates. However, meteorological approaches are often impractical to implement in sites with sparse and diverse vegetation composition, especially with seasonally variable leaf canopy features. Ground‐based infrared thermometry (TIR) provides spatially and temporally continuous resolution of surface skin temperature that can be directly related to the land surface energy balance. We made repeated measurements with a portable TIR camera to capture seasonal replicates for patch scale heat images for four sagebrush communities. The heat images near peak foliage and near the end of the growing season were compared by computation of surface energy fluxes from TIR sensing to surface energy balance (SEB) and Bowen ratio (BR). Estimates of sensible (
Vegetation phenology is a key control on water, energy, and carbon fluxes in terrestrial ecosystems. Because vegetation canopies are heterogeneous, spatially explicit information related to seasonality in vegetation activity provides valuable information for studies that use eddy covariance measurements to study ecosystem function and land-atmosphere interactions. Here we present a land surface phenology (LSP) dataset derived at 3 m spatial resolution from PlanetScope imagery across a range of plant functional types and climates in North America. The dataset provides spatially explicit information related to the timing of phenophase changes such as the start, peak, and end of vegetation activity, along with vegetation index metrics and associated quality assurance flags for the growing seasons of 2017–2021 for 10 × 10 km windows centred over 104 eddy covariance towers at AmeriFlux and National Ecological Observatory Network (NEON) sites. These LSP data can be used to analyse processes controlling the seasonality of ecosystem-scale carbon, water, and energy fluxes, to evaluate predictions from land surface models, and to assess satellite-based LSP products.
more » « less- NSF-PAR ID:
- 10381705
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Scientific Data
- Volume:
- 9
- Issue:
- 1
- ISSN:
- 2052-4463
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract H ) and latent heat flux (LE ) were evaluated with eddy covariance measurements to disaggregate the expression of seasonal phenology of sagebrush species across wetness and elevation. Estimations showed reasonable agreement with ground‐basedLE observations for most cases (r 2 = 0.59–0.76 for SEB and 0.22–0.72 for BR; root mean squared error = 73.4–106.4 W m−2for SEB and 109.9–204.0 W m−2for BR). Predictability declined as the fraction of senescent foliage increased in dry conditions. The field trials suggest the methods have the potential for monitoring land surface energy fluxes and plant health at a very fine spatial scale. The ability to partition heat fluxes from various plant communities over a range of moisture availability will provide valuable information associated with the consumptive water use and phenological processes in the semiarid West. -
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Abstract Robust carbon monitoring systems are needed for land managers to assess and mitigate the changing effects of ecosystem stress on western United States forests, where most aboveground carbon is stored in mountainous areas. Atmospheric carbon uptake via gross primary productivity (GPP) is an important indicator of ecosystem function and is particularly relevant to carbon monitoring systems. However, limited ground-based observations in remote areas with complex topography represent a significant challenge for tracking regional-scale GPP. Satellite observations can help bridge these monitoring gaps, but the accuracy of remote sensing methods for inferring GPP is still limited in montane evergreen needleleaf biomes, where (a) photosynthetic activity is largely decoupled from canopy structure and chlorophyll content, and (b) strong heterogeneity in phenology and atmospheric conditions is difficult to resolve in space and time. Using monthly solar-induced chlorophyll fluorescence (SIF) sampled at ∼4 km from the TROPOspheric Monitoring Instrument (TROPOMI), we show that high-resolution satellite-observed SIF followed ecological expectations of seasonal and elevational patterns of GPP across a 3000 m elevation gradient in the Sierra Nevada mountains of California. After accounting for the effects of high reflected radiance in TROPOMI SIF due to snow cover, the seasonal and elevational patterns of SIF were well correlated with GPP estimates from a machine-learning model (FLUXCOM) and a land surface model (CLM5.0-SP), outperforming other spectral vegetation indices. Differences in the seasonality of TROPOMI SIF and GPP estimates were likely attributed to misrepresentation of moisture limitation and winter photosynthetic activity in FLUXCOM and CLM5.0 respectively, as indicated by discrepancies with GPP derived from eddy covariance observations in the southern Sierra Nevada. These results suggest that satellite-observed SIF can serve as a useful diagnostic and constraint to improve upon estimates of GPP toward multiscale carbon monitoring systems in montane, evergreen conifer biomes at regional scales.
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null (Ed.)High-quality retrieval of land surface phenology (LSP) is increasingly important for understanding the effects of climate change on ecosystem function and biosphere–atmosphere interactions. We analyzed four state-of-the-art phenology methods: threshold, logistic-function, moving-average and first derivative based approaches, and retrieved LSP in the North Hemisphere for the period 1999–2017 from Copernicus Global Land Service (CGLS) SPOT-VEGETATION and PROBA-V leaf area index (LAI) 1 km V2.0 time series. We validated the LSP estimates with near-surface PhenoCam and eddy covariance FLUXNET data over 80 sites of deciduous forests. Results showed a strong correlation (R2 > 0.7) between the satellite LSP and ground-based observations from both PhenoCam and FLUXNET for the timing of the start (SoS) and R2 > 0.5 for the end of season (EoS). The threshold-based method performed the best with a root mean square error of ~9 d with PhenoCam and ~7 d with FLUXNET for the timing of SoS (30th percentile of the annual amplitude), and ~12 d and ~10 d, respectively, for the timing of EoS (40th percentile).more » « less
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null (Ed.)Abstract. Methane (CH4) emissions from natural landscapes constituteroughly half of global CH4 contributions to the atmosphere, yet largeuncertainties remain in the absolute magnitude and the seasonality ofemission quantities and drivers. Eddy covariance (EC) measurements ofCH4 flux are ideal for constraining ecosystem-scale CH4emissions due to quasi-continuous and high-temporal-resolution CH4flux measurements, coincident carbon dioxide, water, and energy fluxmeasurements, lack of ecosystem disturbance, and increased availability ofdatasets over the last decade. Here, we (1) describe the newly publisheddataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset ofCH4 EC measurements (available athttps://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4includes half-hourly and daily gap-filled and non-gap-filled aggregatedCH4 fluxes and meteorological data from 79 sites globally: 42freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drainedecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverageglobally because the majority of sites in FLUXNET-CH4 Version 1.0 arefreshwater wetlands which are a substantial source of total atmosphericCH4 emissions; and (3) we provide the first global estimates of theseasonal variability and seasonality predictors of freshwater wetlandCH4 fluxes. Our representativeness analysis suggests that thefreshwater wetland sites in the dataset cover global wetland bioclimaticattributes (encompassing energy, moisture, and vegetation-relatedparameters) in arctic, boreal, and temperate regions but only sparselycover humid tropical regions. Seasonality metrics of wetland CH4emissions vary considerably across latitudinal bands. In freshwater wetlands(except those between 20∘ S to 20∘ N) the spring onsetof elevated CH4 emissions starts 3 d earlier, and the CH4emission season lasts 4 d longer, for each degree Celsius increase in meanannual air temperature. On average, the spring onset of increasing CH4emissions lags behind soil warming by 1 month, with very few sites experiencingincreased CH4 emissions prior to the onset of soil warming. Incontrast, roughly half of these sites experience the spring onset of risingCH4 emissions prior to the spring increase in gross primaryproductivity (GPP). The timing of peak summer CH4 emissions does notcorrelate with the timing for either peak summer temperature or peak GPP.Our results provide seasonality parameters for CH4 modeling andhighlight seasonality metrics that cannot be predicted by temperature or GPP(i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resourcefor diagnosing and understanding the role of terrestrial ecosystems andclimate drivers in the global CH4 cycle, and future additions of sitesin tropical ecosystems and site years of data collection will provide addedvalue to this database. All seasonality parameters are available athttps://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021).Additionally, raw FLUXNET-CH4 data used to extract seasonality parameterscan be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a completelist of the 79 individual site data DOIs is provided in Table 2 of this paper.more » « less
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Abstract Evapotranspiration (
ET ) is a significant ecosystem flux, governing the partitioning of energy at the land surface. Understanding the seasonal pattern and magnitude ofET is critical for anticipating a range of ecosystem impacts, including drought, heat‐wave events, and plant mortality. In this study, we identified the relative controls of seasonal variability inET , and how these controls vary among ecosystems. We used overlapping AmeriFlux and PhenoCam time series at a daily timestep from 20 sites to explore these linkages (# site‐years >100), and our study area covered a broad climatological aridity gradient in the U.S. and Canada. We focused on disentangling the most important controls of bulk surface conductance (G s) and evaporative fraction (EF =LE /[H +LE ]), whereLE andH represent latent and sensible heat fluxes, respectively. Specifically, we investigated how vegetation phenology varied in importance relative to meteorological variables (vapor pressure deficit and antecedent precipitation) as a driver ofG sandEF using path analysis, a framework for quantifying and comparing the causal linkages among multiple response and explanatory variables. Our results revealed that the drivers ofG sandEF seasonality varied significantly between energy‐ and water‐limited ecosystems. Specifically, precipitation had a much higher effect in water‐limited ecosystems, while seasonal patterns in canopy greenness emerged as a stronger control in energy‐limited ecosystems. Given that phenology is expected to shift under future climate, our findings provide key information for understanding and predicting how phenology may impact 21st‐century hydroclimate regimes and the surface‐energy balance.
