Department of Earth and Environmental Sciences
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Item A global synthesis of transpiration rate and evapotranspiration partitioning in the shrub ecosystems(Elsevier, 2022-03) Gao, Guangyao; Wang, Di; Zha, Tianshan; Wang, Lixin; Fu, Bojie; Earth and Environmental Sciences, School of ScienceTranspiration (T) is a fundamental process in understanding the ecophysiology of plants, and it is the dominant component of evapotranspiration (ET) in the terrestrial water cycle. Although previous studies have examined T characteristics of shrub ecosystems in some regions, global-scale synthesis that integrates the spatial variations of T, ET and ratio of T to ET (T/ET) and the associated influences of bio-/abiotic factors in the shrub ecosystems is currently lacking. In this study, we synthesized and analyzed T rate, ET rate and T/ET of the shrub ecosystems from the peer-reviewed articles using field observations around the world. These studies were mainly distributed in drylands with aridity index (ratio of precipitation to potential ET) < 0.65, which accounted for 86.4% of the study locations. Globally, the mean daily T and ET rates of shrubs were 1.5 ± 1.0 mm d−1 and 2.4 ± 0.8 mm d−1, with coefficient of variation of 63.2% and 36.2% among the study locations, respectively. Mean T/ET of the shrubs over the growing season was 0.54 ± 0.14, which was generally lower compared with forest, grassland and cropland ecosystems. The T rate of shrubs was positively related to shrub age, shrub height, leaf area index, and vegetation coverage (p < 0.05), and the effects of biotic factors on T rate were stronger compared with abiotic factors. The ET rate of shrubs was positively related to aridity index, long-term annual mean precipitation, mean soil water content, as well as shrub height and vegetation coverage (p < 0.05). By contrast, the effects of biotic factors on variations of shrub T/ET were weaker than those of abiotic factors, and the T/ET of shrubs was negatively related to aridity index, long-term annual mean precipitation and mean soil water content, but positively related to latitude (p < 0.05). This study is an important supplement of our knowledge gap in terrestrial water cycle, and the findings suggest that T accounted for about half of the water into atmosphere from shrub ecosystems, and the variations of T rate of shrubs were mainly controlled by biotic factors, whereas ET rate and T/ET was mainly affected by abiotic factors.Item A Landsat-derived annual inland water clarity dataset of China between 1984 and 2018(Copernicus, 2022-01-13) Tao, Hui; Song, Kaishan; Liu, Ge; Wang, Qiang; Wen, Zhidan; Jacinthe, Pierre-Andre; Xu, Xiaofeng; Du, Jia; Shang, Yingxin; Li, Sijia; Wang, Zongming; Lyu, Lili; Hou, Junbin; Wang, Xiang; Liu, Dong; Shi, Kun; Zhang, Baohua; Duan, Hongtao; Earth and Environmental Sciences, School of ScienceWater clarity serves as a sensitive tool for understanding the spatial pattern and historical trend in lakes' trophic status. Despite the wide availability of remotely sensed data, this metric has not been fully explored for long-term environmental monitoring. To this end, we utilized Landsat top-of-atmosphere reflectance products within Google Earth Engine in the period 1984–2018 to retrieve the average Secchi disk depth (SDD) for each lake in each year. Three SDD datasets were used for model calibration and validation from different field campaigns mainly conducted during 2004–2018. The red blue band ratio algorithm was applied to map SDD for lakes (>0.01 km2) based on the first SDD dataset, where R2=0.79 and relative RMSE (rRMSE) =61.9 %. The other two datasets were used to validate the temporal transferability of the SDD estimation model, which confirmed the stable performance of the model. The spatiotemporal dynamics of SDD were analyzed at the five lake regions and individual lake scales, and the average, changing trend, lake number and area, and spatial distribution of lake SDDs across China were presented. In 2018, we found the number of lakes with SDD <2 m accounted for the largest proportion (80.93 %) of the total lakes, but the total areas of lakes with SDD of <0.5 and >4 m were the largest, both accounting for about 24.00 % of the total lakes. During 1984–2018, lakes in the Tibetan–Qinghai Plateau region (TQR) had the clearest water with an average value of 3.32±0.38 m, while that in the northeastern region (NLR) exhibited the lowest SDD (mean 0.60±0.09 m). Among the 10 814 lakes with SDD results for more than 10 years, 55.42 % and 3.49 % of lakes experienced significant increasing and decreasing trends, respectively. At the five lake regions, except for the Inner Mongolia–Xinjiang region (MXR), more than half of the total lakes in every other region exhibited significant increasing trends. In the eastern region (ELR), NLR and Yungui Plateau region (YGR), almost more than 50 % of the lakes that displayed increase or decrease in SDD were mainly distributed in the area range of 0.01–1 km2, whereas those in the TQR and MXR were primarily concentrated in large lakes (>10 km2). Spatially, lakes located in the plateau regions generally exhibited higher SDD than those situated in the flat plain regions. The dataset is freely available at the National Tibetan Plateau Data Center (https://doi.org/10.11888/Hydro.tpdc.271571, Tao et al., 2021).Item A new, lower threshold for lead poisoning in children means more kids will get tested – but the ultimate solution is eliminating lead sources(The Conversation US, Inc., 2021-11-05) Filippelli, Gabriel; Earth and Environmental Sciences, School of ScienceItem Abiotic processes are insufficient for fertile island development: A ten‐year artificial shrub experiment in a desert grassland(Wiley, 2017) Li, Junran; Gilhooly, William P., III; Okin, Gregory S.; Blackwell, John; Department of Earth Sciences, School of ScienceThe relative importance of biotic and abiotic processes in the development of “fertile islands” in dryland systems has rarely been investigated. Here we approached this question by using artificial shrubs, which exclude plant litter production and soil nutrient uptake, but retain the functions of trapping windblown material, funneling of stemflow, and differential rain splash. We conducted a vegetation manipulation study more than a decade ago in the desert grassland of southern New Mexico and subsequently revisited the site in 2012 and 2015. The results show that no notable soil mounds were observed under the artificial shrubs; however, soil texture under the artificial shrubs has gradually changed to resemble the patterns of soil particle-size distribution under natural shrubs. Our results highlight that with the exclusion of direct biotic additions, soils captured by shrub canopies are not necessarily fertile and thus do not themselves contribute to the development of fertile islands.Item Acetoclastic Methanosaeta are dominant methanogens in organic-rich Antarctic marine sediments(Springer Nature, 2018-02) Carr, Stephanie A.; Schubotz, Florence; Dunbar, Robert B.; Mills, Christopher T.; Dias, Robert; Summons, Roger E.; Mandernack, Kevin W.; Earth Sciences, School of ScienceDespite accounting for the majority of sedimentary methane, the physiology and relative abundance of subsurface methanogens remain poorly understood. We combined intact polar lipid and metagenome techniques to better constrain the presence and functions of methanogens within the highly reducing, organic-rich sediments of Antarctica's Adélie Basin. The assembly of metagenomic sequence data identified phylogenic and functional marker genes of methanogens and generated the first Methanosaeta sp. genome from a deep subsurface sedimentary environment. Based on structural and isotopic measurements, glycerol dialkyl glycerol tetraethers with diglycosyl phosphatidylglycerol head groups were classified as biomarkers for active methanogens. The stable carbon isotope (δ13C) values of these biomarkers and the Methanosaeta partial genome suggest that these organisms are acetoclastic methanogens and represent a relatively small (0.2%) but active population. Metagenomic and lipid analyses suggest that Thaumarchaeota and heterotrophic bacteria co-exist with Methanosaeta and together contribute to increasing concentrations and δ13C values of dissolved inorganic carbon with depth. This study presents the first functional insights of deep subsurface Methanosaeta organisms and highlights their role in methane production and overall carbon cycling within sedimentary environments.Item Addressing Pollution-Related Global Environmental Health Burdens(AGU, 2018-02-19) Filippelli, Gabriel M.; Taylor, Mark P.; Earth Sciences, School of ScienceNew analyses are revealing the scale of pollution on global health, with a disproportionate share of the impact borne by lower‐income nations, minority and marginalized individuals. Common themes emerge on the drivers of this pollution impact, including a lack of regulation and its enforcement, research and expertise development, and innovative funding mechanisms for mitigation. Creative approaches need to be developed and applied to address and overcome these obstacles. The existing “business as usual” modus operandi continues to externalize human health costs related to pollution, which exerts a negative influence on global environmental health.Item Addressing the Need for Just GeoHealth Engagement: Evolving Models for Actionable Research That Transform Communities(AGU, 2021-12) Hayhow, Claire M.; Brabander, Dan J.; Jim, Rebecca; Lively, Martin; Filippelli, Gabriel M.; Earth Sciences, School of ScienceGeoHealth as a research paradigm offers the opportunity to re-evaluate common research engagement models and science training practices. GeoHealth challenges are often wicked problems that require both transdisciplinary approaches and the establishment of intimate and long-term partnerships with a range of community members. We examine four common modes of community engagement and explore how research projects are launched, who has the power in these relationships, and how projects evolve to become truly transformative for everyone involved.Item Advances and limitations of using satellites to monitor cyanobacterial harmful algal blooms(Associação Brasileira de Limnologia, 2019-06) Ogashawara, Igor; Earth Sciences, School of ScienceThe use of satellites for monitoring forests is common and well-known practice. However, the operational remote monitoring of water quality from space is still under development. In the United States of America (USA), the use of this type of data is just now being applied to operationally monitor cyanobacterial harmful algal blooms (CHABs). This powerful tool can be used to generate temporal and spatial assessments of CHABs, however the validation of the retrieved information is still a challenge - especially in tropical and equatorial countries. This commentary discusses the advantages and challenges of current initiatives that use Earth Observation data for managing CHABs such as “Lake Erie’s HAB Bulletin” and “Project CYAN” - both in the USA. Additionally, it was also discussed the application of remote sensing techniques to monitor CHABs in Brazilian inland waters.Item Advancing cyanobacteria biomass estimation from hyperspectral observations: Demonstrations with HICO and PRISMA imagery(Elsevier, 2021-12) O'Shea, Ryan E.; Pahlevan, Nima; Smith, Brandon; Bresciani, Mariano; Egerton, Todd; Giardino, Claudia; Li, Lin; Moore, Tim; Ruiz-Verdu, Antonio; Ruberg, Steve; Simis, Stefan G. H.; Stumpf, Richard; Vaičiūtė, Diana; Earth Sciences, School of ScienceRetrieval of the phycocyanin concentration (PC), a characteristic pigment of, and proxy for, cyanobacteria biomass, from hyperspectral satellite remote sensing measurements is challenging due to uncertainties in the remote sensing reflectance (∆Rrs) resulting from atmospheric correction and instrument radiometric noise. Although several individual algorithms have been proven to capture local variations in cyanobacteria biomass in specific regions, their performance has not been assessed on hyperspectral images from satellite sensors. Our work leverages a machine-learning model, Mixture Density Networks (MDNs), trained on a large (N = 939) dataset of collocated in situ chlorophyll-a concentrations (Chla), PCs, and remote sensing reflectance (Rrs) measurements to estimate PC from all relevant spectral bands. The performance of the developed model is demonstrated via PC maps produced from select images of the Hyperspectral Imager for the Coastal Ocean (HICO) and Italian Space Agency's PRecursore IperSpettrale della Missione Applicativa (PRISMA) using a matchup dataset. As input to the MDN, we incorporate a combination of widely used band ratios (BRs) and line heights (LHs) taken from existing multispectral algorithms, that have been proven for both Chla and PC estimation, as well as novel BRs and LHs to increase the overall cyanobacteria biomass estimation accuracy and reduce the sensitivity to ∆Rrs. When trained on a random half of the dataset, the MDN achieves uncertainties of 44.3%, which is less than half of the uncertainties of all viable optimized multispectral PC algorithms. The MDN is notably better than multispectral algorithms at preventing overestimation on low (<10 mg m−3) PC. Visibly, HICO and PRISMA PC maps show the wider dynamic range that can be represented by the MDN. The available in situ and satellite-derived Rrs matchups and measured in situ PC demonstrate the robustness of the MDN for estimating low (<10 mg m−3) PC and the reduced impact of ∆Rrs on medium-to-high in situ PC (>10 mg m−3). According to our extensive assessments, the developed model is anticipated to enable practical PC products from PRISMA and HICO, therefore the model is promising for planned hyperspectral missions, such as the Plankton Aerosol and Cloud Ecosystem (PACE). This advancement will enhance the complementary roles of hyperspectral radiometry from satellite and low-altitude platforms for quantifying and monitoring cyanobacteria harmful algal blooms at both large and local spatial scales.Item African dryland ecosystem changes controlled by soil water(Wiley, 2019-08) Wei, Fangli; Wang, Shuai; Fu, Bojie; Wang, Lixin; Liu, Yi Y.; Li, Yan; Earth Sciences, School of ScienceMonitoring long‐term vegetation dynamics in African drylands is of great importance for both ecosystem degradation studies and carbon‐cycle modelling. Here, we exploited the complementary use of optical and passive microwave satellite data— normalized difference vegetation index (NDVI) and vegetation optical depth (VOD)—to provide new insights of ecosystem changes in African drylands. During 1993–2012, 54% of African drylands experienced a significant increase of VOD, mainly located in southern Africa and west and central Africa, with an average rate of increase of (1.2 ± 2.7) × 10−3 yr−1. However, a significant decreasing NDVI was observed over 43% of the African drylands, in particular in western Niger and eastern Africa, with an average browning rate of (−0.13 ± 1.5) × 10−3 yr−1. The contrasting vegetation trends (increasing VOD and decreasing NDVI) were largely caused by an increase in the relative proportion of the woody component of the vegetation, as a result of the prevailing woody encroachment in African drylands during the study period. Soil water emerges as the dominant driver of ecosystem changes in African drylands, in particular in arid and semiarid areas. This is evidenced by a strong spatio‐temporal correlation between soil water and vegetation, where soil water changes explain about 48% of vegetation variations. This study emphasizes the potential of utilizing multiple satellite products with different strengths in monitoring different characteristics of ecosystems to evaluate ecosystem changes and reveal the underlying mechanisms of the observed changes.