Ecosystem functional diversity and the representativeness of environmental networks across the conterminous United States

Villarreal, Samuel; Guevara, Mário; Alcaraz‐Segura, Domingo; Brunsell, Nathaniel A.; Hayes, D. J.; Loescher, Henry W.; Vargas, Rodrigo

doi:10.1016/j.agrformet.2018.07.016

Cited by 41 publications

(53 citation statements)

References 69 publications

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“…However, to improve our understanding of the land‐atmosphere interactions, we propose that it is also needed to include information about ecosystem functionality (Bond‐Lamberty et al, ; Petrakis et al, ; Reichstein et al, ). The addition of information on ecosystem functional attributes has enhanced biodiversity models (Alcaraz‐Segura et al, , ; Armas et al, ) and is useful for network design and assessment (Villarreal et al, ). We argue that including information related to environmental state factors along with ecosystem functional heterogeneity could complement bioclimatic information to define ESAs, since ecosystem‐level observations suggest that climate controls are insufficient to explain land‐atmosphere interactions (Reichstein et al, ).…”

Section: Discussionmentioning

confidence: 99%

“…FLUXNET and associated regional networks (e.g., AmeriFlux, AsiaFlux, and MexFlux) are monitoring net ecosystem exchange and ET worldwide and have improved our understanding of terrestrial biogeochemistry and land‐atmosphere interactions (Baldocchi et al, ). Most of these EONs are organized under a bottom‐up approach, which is prone to overrepresent/underrepresent certain ecosystems, land cover types, or specific ecological conditions (Hargrove et al, ; Kumar et al, ; Sulkava et al, ; Villarreal et al, ). The underrepresentativeness of these EONs is also evident among countries, where developed countries are better represented than developing countries (Kumar et al, ).…”

Section: Introductionmentioning

confidence: 99%

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Optimizing an Environmental Observatory Network Design Using Publicly Available Data

et al. 2019

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There is a need to optimize resources for large‐scale environmental monitoring efforts, especially in developing countries. We tested a flexible framework to optimize the design (i.e., selection of study sites) of an environmental observatory network (EON) using publicly available data for Mexico. This country represents a challenge for designing EONs because of its megadiversity and large climate and ecological heterogeneity. We address three pervasive challenges for designing EONs: (1) How to characterize and delineate ecologically similar areas, (2) how to set geographic priorities to establish new representative study sites, and (3) how to assess the representativeness of current and potential new study sites. We used unsupervised cluster analysis to spatially delineate ecologically similar sampling domains. We identified the most representative sites within each domain using a conditioned Latin Hypercube‐sampling strategy. Finally, we demonstrated the applicability of this approach by assessing the spatial representativeness of the eddy covariance network in Mexico (i.e., MexFlux). At least 84 distributed sampling sites are needed to represent >45% of the spatial heterogeneity of gross primary productivity (GPP) dynamics (i.e., GPP_mean and GPP_cv) and evapotranspiration (ET) dynamics (i.e., ET_mean and ET_cv) at the national level. The current array of MexFlux only represents 3% of GPP and 5% of ET dynamics spatial variability at the national‐level, while the same number of sites organized under an optimal framework nearly doubled these estimates. Our framework is based on a data‐driven approach and publicly available sources of information, so it could be applied anywhere in the world.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimizing an Environmental Observatory Network Design Using Publicly Available Data

et al. 2019

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“…Typically, flux tower networks are used as groundtruth observations to evaluate carbon exchange in process models (Friend et al 2007, Raczka et al 2013 and to inform a priori errors in atmospheric inversions (Chevallier et al 2006). However, individual tower sites are limited in regional representativeness (this work, Villarreal et al 2018), and aircraft EC can provide a valuable supplement with which to examine landscape-scale changes in the underlying drivers of carbon exchange.…”

Section: Comparison To Tower Flux Observationsmentioning

confidence: 99%

“…However, inventory-based estimates have large associated uncertainties of up to 75% (Hayes et al 2018), and discrepancies persist between different modeling approaches (Huntzinger et al 2012, Melton et al 2013 and model-tower data comparisons (Schwalm et al 2010, Schaefer et al 2012. Tower-based flux observations can provide benchmark information and a basis for validation, but their spatial representativeness is very limited at regional to continental scales (Villarreal et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Spatial heterogeneity in CO₂, CH₄, and energy fluxes: insights from airborne eddy covariance measurements over the Mid-Atlantic region

Hannun

Wolfe

Kawa

et al. 2020

Environ. Res. Lett.

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The exchange of carbon between the Earth's atmosphere and biosphere influences the atmospheric abundances of carbon dioxide (CO 2 ) and methane (CH 4 ). Airborne eddy covariance (EC) can quantify surface-atmosphere exchange from landscape-to-regional scales, offering a unique perspective on carbon cycle dynamics. We use extensive airborne measurements to quantify fluxes of sensible heat, latent heat, CO 2 , and CH 4 across multiple ecosystems in the Mid-Atlantic region during September 2016 and May 2017. In conjunction with footprint analysis and land cover information, we use the airborne dataset to explore the effects of landscape heterogeneity on measured fluxes. Our results demonstrate large variability in CO 2 uptake over mixed agricultural and forested sites, with fluxes ranging from −3.4±0.7 to −11.5±1.6 μmol m −2 s −1 for croplands and −9.1±1.5 to −22.7±3.2 μmol m −2 s −1 for forests. We also report substantial CH 4 emissions of 32.3±17.0 to 76.1±29.4 nmol m −2 s −1 from a brackish herbaceous wetland and 58.4±12.0 to 181.2± 36.8 nmol m −2 s −1 from a freshwater forested wetland. Comparison of ecosystem-specific aircraft observations with measurements from EC flux towers along the flight path demonstrate that towers capture ∼30%-75% of the regional variability in ecosystem fluxes. Diel patterns measured at the tower sites suggest that peak, midday flux measurements from aircraft accurately predict net daily CO 2 exchange. We discuss next steps in applying airborne observations to evaluate bottom-up flux models and improve understanding of the biophysical processes that drive carbon exchange from landscapeto-regional scales.

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“…Semi‐arid ecosystems occupy approximately̴ 40% of the terrestrial surface and are home to more than 38% of the total global population (Reynolds et al, ), but they are under‐represented in ecological research networks (Reichstein et al, ; Schimel, ; Villarreal et al, ). In these ecosystems, soils play a key role in the uptake and emissions of the main greenhouse gases (Ahlström et al, ; Poulter et al, ).…”

Section: Introductionmentioning

confidence: 99%

CO₂ Dynamics Are Strongly Influenced by Low Frequency Atmospheric Pressure Changes in Semiarid Grasslands

et al. 2019

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Due to their large carbon storage capacity and ability to exchange subterranean CO 2 with the atmosphere, soils are key components in the carbon balance in semi-arid ecosystems. Most studies have focused on shallow (e.g., <30 cm depth) soil CO 2 dynamics neglecting processes in deeper soil layers where highly CO 2 -enriched air can be stored or transported through soil pores and fissures. Here, we examine the relationship among variations in subterranean CO 2 molar fraction, volumetric water content, soil temperature and atmospheric pressure during three years within soil profiles (0.15, 0.50, and 1.50 m depths) in two semi-arid grasslands located in southeastern Spain. We applied a wavelet coherence analysis to study the temporal variability and temporal correlation between the CO 2 molar fraction and its covariates (soil temperature, soil moisture and atmospheric pressure). Our results show that CO 2 dynamics are strongly influenced by changes in atmospheric pressure from semidiurnal, diurnal and synoptic to monthly time-scales for all soil depths. In contrast, only weak daily dependencies were found at the surface level (0.15 m) regarding soil temperature and volumetric water content. Atmospheric pressure changes substantially influence variations in the CO 2 content (with daily fluctuations of up to 2000 ppm) denoting transportation through soil layers. These results provide insights into the importance of subterranean storage and non-diffusive gas transport that could influence soil CO 2 efflux rates, processes that are not considered when applying the flux-gradient approach and, which can be especially important in ecosystems with high air permeability between the unsaturated porous media and the atmosphere.Plain Language Summary Each type of ecosystem has a role in the balance of atmospheric greenhouse gases, acting as either sink or source. Semi-arid ecosystems occupy approximately 40% of the terrestrial surface and dominate the trend and variability of the land CO 2 sink. The roles played by such ecosystems remain under-investigated, and the resulting lack of knowledge undermines future predictions of global environmental change. This study shows that underground CO 2 dynamics in two semi-arid ecosystems are strongly influenced by changes in atmospheric pressure (with strong daily fluctuations), while only weak dependencies were found regarding soil temperature and water content (factors that affect biologic activity). The atmospheric pressure effect on the soil CO 2 concentration was more evident when the air permeability between atmosphere and soil surface was higher. Soil CO 2 variations forced by changes in atmospheric pressure occur consistently from semidiurnal to monthly time-scales. These observations will help to improve the current models that assume soil temperature and moisture to be the main drivers of soil CO 2 dynamics, but are mistakenly applied in semi-arid ecosystems.

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Ecosystem functional diversity and the representativeness of environmental networks across the conterminous United States

Cited by 41 publications

References 69 publications

Optimizing an Environmental Observatory Network Design Using Publicly Available Data

Optimizing an Environmental Observatory Network Design Using Publicly Available Data

Spatial heterogeneity in CO₂, CH₄, and energy fluxes: insights from airborne eddy covariance measurements over the Mid-Atlantic region

CO₂ Dynamics Are Strongly Influenced by Low Frequency Atmospheric Pressure Changes in Semiarid Grasslands

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Ecosystem functional diversity and the representativeness of environmental networks across the conterminous United States

Cited by 41 publications

References 69 publications

Optimizing an Environmental Observatory Network Design Using Publicly Available Data

Optimizing an Environmental Observatory Network Design Using Publicly Available Data

Spatial heterogeneity in CO2, CH4, and energy fluxes: insights from airborne eddy covariance measurements over the Mid-Atlantic region

CO2 Dynamics Are Strongly Influenced by Low Frequency Atmospheric Pressure Changes in Semiarid Grasslands

Contact Info

Product

Resources

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Spatial heterogeneity in CO₂, CH₄, and energy fluxes: insights from airborne eddy covariance measurements over the Mid-Atlantic region

CO₂ Dynamics Are Strongly Influenced by Low Frequency Atmospheric Pressure Changes in Semiarid Grasslands