Synergistic use of SMAP and OCO-2 data in assessing the responses of ecosystem productivity to the 2018 U.S. drought

Soil moisture and gross primary productivity (GPP) estimates from the Soil Moisture Active Passive (SMAP) and solar-induced chlorophyll fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2) provide new opportunities for understanding the relationship between soil moisture and terrestrial photosynthesis over large regions. Here we explored the potential of the synergistic use of SMAP and OCO-2 based data for monitoring the responses of ecosystem productivity to drought. We used complementary observational information on root-zone soil moisture and GPP (9 km) from SMAP and fine-resolution SIF (0.05°; GOSIF) derived from OCO-2 SIF soundings. We compared the spatial pattern and temporal evolution of anomalies of these variables over the conterminous U.S. during the 2018 drought, and examined to what extent they could characterize the drought-induced variations of flux tower GPP and crop yield data. Our results showed that SMAP GPP and GOSIF, both freely available online, could well capture the spatial extent and dynamics of the impacts of drought indicated by the U.S. Drought Monitor maps and the SMAP root-zone soil moisture deficit. Over the U.S. Southwest, monthly anomalies of soil moisture showed significant positive correlations with those of SMAP GPP (R² = 0.44, p < 0.001) and GOSIF (R² = 0.76, p < 0.001), demonstrating strong water availability constraints on plant productivity across dryland ecosystems. We further found that SMAP GPP and GOSIF captured the impact of drought on tower GPP and crop yield. Our results suggest that synergistic use of SMAP and OCO-2 data products can reveal the drought evolution and its impact on ecosystem productivity and carbon uptake at multiple spatial and temporal scales, and demonstrate the value of SMAP and OCO-2 for studying ecosystem function, carbon cycling, and climate change

Synergistic use of SMAP and OCO-2 data in assessing the responses of ecosystem productivity to the 2018 U.S. drought

Soil moisture and gross primary productivity (GPP) estimates from the Soil Moisture Active Passive (SMAP) and solar-induced chlorophyll fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2) provide new opportunities for understanding the relationship between soil moisture and terrestrial photosynthesis over large regions. Here we explored the potential of the synergistic use of SMAP and OCO-2 based data for monitoring the responses of ecosystem productivity to drought. We used complementary observational information on root-zone soil moisture and GPP (9 km) from SMAP and fine-resolution SIF (0.05°; GOSIF) derived from OCO-2 SIF soundings. We compared the spatial pattern and temporal evolution of anomalies of these variables over the conterminous U.S. during the 2018 drought, and examined to what extent they could characterize the drought-induced variations of flux tower GPP and crop yield data. Our results showed that SMAP GPP and GOSIF, both freely available online, could well capture the spatial extent and dynamics of the impacts of drought indicated by the U.S. Drought Monitor maps and the SMAP root-zone soil moisture deficit. Over the U.S. Southwest, monthly anomalies of soil moisture showed significant positive correlations with those of SMAP GPP (R² = 0.44, p < 0.001) and GOSIF (R² = 0.76, p < 0.001), demonstrating strong water availability constraints on plant productivity across dryland ecosystems. We further found that SMAP GPP and GOSIF captured the impact of drought on tower GPP and crop yield. Our results suggest that synergistic use of SMAP and OCO-2 data products can reveal the drought evolution and its impact on ecosystem productivity and carbon uptake at multiple spatial and temporal scales, and demonstrate the value of SMAP and OCO-2 for studying ecosystem function, carbon cycling, and climate change

The sensitivity of carbon exchanges in Great Plains grasslands to precipitation variability

In the Great Plains, grassland carbon dynamics differ across broad gradients of precipitation and temperature, yet finer-scale variation in these variables may also affect grassland processes. Despite the importance of grasslands, there is little information on how fine-scale relationships compare between them regionally. We compared grassland C exchanges, energy partitioning and precipitation variability in eight sites in the eastern and western Great Plains using eddy covariance and meteorological data. During our study, both eastern and western grasslands varied between an average net carbon sink and a net source. Eastern grasslands had a moderate vapor pressure deficit (VPD = 0.95 kPa) and high growing season gross primary productivity (GPP = 1010 ± 218 g C m−2 yr−1). Western grasslands had a growing season with higher VPD (1.43 kPa) and lower GPP (360 ± 127 g C m−2 yr−1). Western grasslands were sensitive to precipitation at daily timescales, whereas eastern grasslands were sensitive at monthly and seasonal timescales. Our results support the expectation that C exchanges in these grasslands differ as a result of varying precipitation regimes. Because eastern grasslands are less influenced by short-term variability in rainfall than western grasslands, the effects of precipitation change are likely to be more predictable in eastern grasslands because the timescales of variability that must be resolved are relatively longer. We postulate increasing regional heterogeneity in grassland C exchanges in the Great Plains in coming decades.Konza Prairie Biological Station. Grant Number: DEB-0823341U.S. Department of Energy. Grant Number: DE-AC02-05CH11231U.S. Department of Agriculture. Grant Number: 2014-67003-22070DOE-NIGEC. Grant Number: 26-6223-7230-002Natural Sciences and Engineering Research Council of Canada Discovery. Grant Number: RGPIN-2014-05882Sevilleta LTERNAS

Differential effects of extreme drought on production and respiration: synthesis and modeling analysis

This is the published version, also available here: http://dx.doi.org/10.5194/bg-11-621-2014, 2014.Extremes in climate may severely impact ecosystem structure and function, with both the magnitude and rate of response differing among ecosystem types and processes. We conducted a modeling analysis of the effects of extreme drought on two key ecosystem processes, production and respiration, and, to provide a broader context, we complemented this with a synthesis of published results that cover a wide variety of ecosystems. The synthesis indicated that across a broad range of biomes, gross primary production (GPP) was generally more sensitive to extreme drought (defined as proportional reduction relative to average rainfall periods) than was ecosystem respiration (ER). Furthermore, this differential sensitivity between production and respiration increased as drought severity increased; it occurred only in grassland ecosystems, and not in evergreen needle-leaf and broad-leaf forests or woody savannahs. The modeling analysis was designed to enable a better understanding of the mechanisms underlying this pattern, and focused on four grassland sites arrayed across the Great Plains, USA. Model results consistently showed that net primary productivity (NPP) was reduced more than heterotrophic respiration (Rh) by extreme drought (i.e., 67% reduction in annual ambient rainfall) at all four study sites. The sensitivity of NPP to drought was directly attributable to rainfall amount, whereas the sensitivity of Rh to drought was driven by soil drying, reduced carbon (C) input and a drought-induced reduction in soil C content – a much slower process. However, differences in reductions in NPP and Rh diminished as extreme drought continued, due to a gradual decline in the soil C pool leading to further reductions in Rh. We also varied the way in which drought was imposed in the modeling analysis; it was either imposed by simulating reductions in rainfall event size (ESR) or by reducing rainfall event number (REN). Modeled NPP and Rh decreased more by ESR than REN at the two relatively mesic sites but less so at the two xeric sites. Our findings suggest that responses of production and respiration differ in magnitude, occur on different timescales, and are affected by different mechanisms under extreme, prolonged drought

Warm spring reduced carbon cycle impact of the 2012 US summer drought

The global terrestrial carbon sink offsets one-third of the world’s fossil fuel emissions, but the strength of this sink is highly sensitive to large-scale extreme events. In 2012, the contiguous United States experienced exceptionally warm temperatures and the most severe drought since the Dust Bowl era of the 1930s, resulting in substantial economic damage. It is crucial to understand the dynamics of such events because warmer temperatures and a higher prevalence of drought are projected in a changing climate. Here, we combine an extensive network of direct ecosystem flux measurements with satellite remote sensing and atmospheric inverse modeling to quantify the impact of the warmer spring and summer drought on biosphere-atmosphere carbon and water exchange in 2012. We consistently find that earlier vegetation activity increased spring carbon uptake and compensated for the reduced uptake during the summer drought, which mitigated the impact on net annual carbon uptake. The early phenological development in the Eastern Temperate Forests played a major role for the continental-scale carbon balance in 2012. The warm spring also depleted soil water resources earlier, and thus exacerbated water limitations during summer. Our results show that the detrimental effects of severe summer drought on ecosystem carbon storage can be mitigated by warming-induced increases in spring carbon uptake. However, the results also suggest that the positive carbon cycle effect of warm spring enhances water limitations and can increase summer heating through biosphere–atmosphere feedbacks.Data deposition: The eddy-covariance data are available in the AmeriFlux data archive at the Carbon Dioxide Information Analysis Center at the Oak Ridge National Laboratory (cdiac.ornl.gov/ftp/ameriflux/data). This is the publisher’s final pdf. The article is published by National Academy of Sciences and can be found at: http://www.pnas.org/Keywords: ecosystem fluxes, eddy covariance, carbon uptake, biosphere, seasonal climate anomalies, atmosphere feedback

SoDaH: the SOils DAta Harmonization database, an open-source synthesis of soil data from research networks, version 1.0

Data collected from research networks present opportunities to test theories and develop models about factors responsible for the long-term persistence and vulnerability of soil organic matter (SOM). Synthesizing datasets collected by different research networks presents opportunities to expand the ecological gradients and scientific breadth of information available for inquiry. Synthesizing these data is challenging, especially considering the legacy of soil data that have already been collected and an expansion of new network science initiatives. To facilitate this effort, here we present the SOils DAta Harmonization database (SoDaH; https://lter.github.io/som-website, last access: 22 December 2020), a flexible database designed to harmonize diverse SOM datasets from multiple research networks. SoDaH is built on several network science efforts in the United States, but the tools built for SoDaH aim to provide an open-access resource to facilitate synthesis of soil carbon data. Moreover, SoDaH allows for individual locations to contribute results from experimental manipulations, repeated measurements from long-term studies, and local- to regional-scale gradients across ecosystems or landscapes. Finally, we also provide data visualization and analysis tools that can be used to query and analyze the aggregated database. The SoDaH v1.0 dataset is archived and available at https://doi.org/10.6073/pasta/9733f6b6d2ffd12bf126dc36a763e0b4 (Wieder et al., 2020)

The importance of monsoon precipitation for foundation tree species across the semiarid Southwestern U.S.

Forest dynamics in arid and semiarid regions are sensitive to water availability, which is becoming increasingly scarce as global climate changes. The timing and magnitude of precipitation in the semiarid southwestern U.S. (“Southwest”) has changed since the 21st century began. The region is projected to become hotter and drier as the century proceeds, with implications for carbon storage, pest outbreaks, and wildfire resilience. Our goal was to quantify the importance of summer monsoon precipitation for forested ecosystems across this region. We developed an isotope mixing model in a Bayesian framework to characterize summer (monsoon) precipitation soil water recharge and water use by three foundation tree species (Populus tremuloides [aspen], Pinus edulis [piñon], and Juniperus osteosperma [Utah juniper]). In 2016, soil depths recharged by monsoon precipitation and tree reliance on monsoon moisture varied across the Southwest with clear differences between species. Monsoon precipitation recharged soil at piñon-juniper (PJ) and aspen sites to depths of at least 60 cm. All trees in the study relied primarily on intermediate to deep (10-60 cm) moisture both before and after the onset of the monsoon. Though trees continued to primarily rely on intermediate to deep moisture after the monsoon, all species increased reliance on shallow soil moisture to varying degrees. Aspens increased reliance on shallow soil moisture by 13% to 20%. Utah junipers and co-dominant ñons increased their reliance on shallow soil moisture by about 6% to 12%. Nonetheless, approximately half of the post-monsoon moisture in sampled piñon (38-58%) and juniper (47-53%) stems could be attributed to the monsoon. The monsoon contributed lower amounts to aspen stem water (24-45%) across the study area with the largest impacts at sites with recent precipitation. Therefore, monsoon precipitation is a key driver of growing season moisture that semiarid forests rely on across the Southwest. This monsoon reliance is of critical importance now more than ever as higher global temperatures lead to an increasingly unpredictable and weaker North American Monsoon

A Continuous Measure of Gross Primary Production for the Conterminous U.S. Derived from MODIS and AmeriFlux Data

The quantification of carbon fluxes between the terrestrial biosphere and the atmosphere is of scientific importance and also relevant to climate-policy making. Eddy covariance flux towers provide continuous measurements of ecosystem-level exchange of carbon dioxide spanning diurnal, synoptic, seasonal, and interannual time scales. However, these measurements only represent the fluxes at the scale of the tower footprint. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to upscale gross primary productivity (GPP) data from eddy covariance flux towers to the continental scale. We first combined GPP and MODIS data for 42 AmeriFlux towers encompassing a wide range of ecosystem and climate types to develop a predictive GPP model using a regression tree approach. The predictive model was trained using observed GPP over the period 2000-2004, and was validated using observed GPP over the period 2005-2006 and leave-one-out cross-validation. Our model predicted GPP fairly well at the site level. We then used the model to estimate GPP for each 1 km x 1 km cell across the U.S. for each 8-day interval over the period from February 2000 to December 2006 using MODIS data. Our GPP estimates provide a spatially and temporally continuous measure of gross primary production for the U.S. that is a highly constrained by eddy covariance flux data. Our study demonstrated that our empirical approach is effective for upscaling eddy flux GPP data to the continental scale and producing continuous GPP estimates across multiple biomes. With these estimates, we then examined the patterns, magnitude, and interannual variability of GPP. We estimated a gross carbon uptake between 6.91 and 7.33 Pg C yr{sup -1} for the conterminous U.S. Drought, fires, and hurricanes reduced annual GPP at regional scales and could have a significant impact on the U.S. net ecosystem carbon exchange. The sources of the interannual variability of U.S. GPP were dominated by these extreme climate events and disturbances

Thermal optimality of net ecosystem exchange of carbon dioxide and underlying mechanisms

It is well established that individual organisms can acclimate and adapt to temperature to optimize their functioning. However, thermal optimization of ecosystems, as an assemblage of organisms, has not been examined at broad spatial and temporal scales. Here, we compiled data from 169 globally distributed sites of eddy covariance and quantified the temperature response functions of net ecosystem exchange (NEE), an ecosystem-level property, to determine whether NEE shows thermal optimality and to explore the underlying mechanisms. We found that the temperature response of NEE followed a peak curve, with the optimum temperature (corresponding to the maximum magnitude of NEE) being positively correlated with annual mean temperature over years and across sites. Shifts of the optimum temperature of NEE were mostly a result of temperature acclimation of gross primary productivity (upward shift of optimum temperature) rather than changes in the temperature sensitivity of ecosystem respiration. Ecosystem-level thermal optimality is a newly revealed ecosystem property, presumably reflecting associated evolutionary adaptation of organisms within ecosystems, and has the potential to significantly regulate ecosystemclimate change feedbacks. The thermal optimality of NEE has implications for understanding fundamental properties of ecosystems in changing environments and benchmarking global models.This is the publisher’s final pdf. The published article is copyrighted by New Phytologist Trust and can be found at: http://www.newphytologist.org/Keywords: Climate change, Temperature acclimation, Optimum temperature, Thermal optimality, Temperature adaptatio

Supporting data for Allometric relationships for Quercus gambelii (Gambel oak) and Robinia neomexicana (New Mexico locust) for field and remote sensing biomass retrieval in post-disturbance landscapes

----File description---- allometry_data.csv: All of the field measurment data that went into calculating the area and volume to biomass regressions allometry_repo.slides.html: Reveal.js slides for the workflow surrounding the allometry manuscript, including figure generation jemez_allometry_LA.csv: All of the associated leaf weight and leaf scan data used to calculate species specific leaf area JemezAllometry_Workbook.xlsx: Microsoft Excel workbook containing an example application of the allometric equation