Geology topics

Xiao Yang

Publications and source records attributed to Xiao Yang.

12 recordsLinked to original sources

USGS2025

Clarifying the trophic state concept to advance macroscale freshwater science and management

For over a century, ecologists have used the concept of trophic state (TS) to characterize an aquatic ecosystem's biological productivity. However, multiple TS classification schemes, each relying on a variety of measurable parameters as proxies for productivity, have emerged to meet use-specific needs. Frequently, chlorophyll a, phosphorus, and Secchi depth are used to classify TS based on autotrophic production, whereas phosphorus, dissolved organic carbon, and true color are used to classify TS based on both autotrophic and heterotrophic production. Both classification approaches aim to characterize an ecosystem's function broadly, but with varying degrees of autotrophic and heterotrophic processes considered in those characterizations. Moreover, differing classification schemes can create inconsistent interpretations of ecosystem integrity. For example, the US Clean Water Act focuses exclusively on algal threats to water quality, framed in terms of eutrophication in response to nutrient loading. This usage lacks information about non-algal threats to water quality, such as dystrophication in response to dissolved organic carbon loading. Consequently, the TS classification schemes used to identify eutrophication and dystrophication may refer to ecosystems similarly (e.g., oligotrophic and eutrophic), yet these categories are derived from different proxies. These inconsistencies in TS classification schemes may be compounded when interdisciplinary projects employ varied TS frameworks. Even with these shortcomings, TS can still be used to distill information on complex aquatic ecosystem function into a set of generalizable expectations. The usefulness of distilling complex information into a TS index is substantial such that usage inconsistencies should be explicitly addressed and resolved. To emphasize the consequences of diverging TS classification schemes, we present three case studies for which an improved understanding of the TS concept advances freshwater research, management efforts, and interdisciplinary collaboration. To increase clarity in TS, the aquatic sciences could benefit from including information about the proxy variables, ecosystem type, as well as the spatiotemporal domains used to classify TS. As the field of aquatic sciences expands and climatic irregularity increases, we highlight the importance of re-evaluating fundamental concepts, such as TS, to ensure their compatibility with evolving science.

Ecosphere↗

USGS2025

One-hundred fundamental, open questions to integrate methodological approaches in lake ice research

The rate of technological innovation within aquatic sciences outpaces the collective ability of individual scientists within the field to make appropriate use of those technologies. The process of in situ lake sampling remains the primary choice to comprehensively understand an aquatic ecosystem at local scales; however, the impact of climate change on lakes necessitates the rapid advancement of understanding and the incorporation of lakes on both landscape and global scales. Three fields driving innovation within winter limnology that we address here are autonomous real-time in situ monitoring, remote sensing, and modeling. The recent progress in low-power in situ sensing and data telemetry allows continuous tracing of under-ice processes in selected lakes as well as the development of global lake observational networks. Remote sensing offers consistent monitoring of numerous systems, allowing limnologists to ask certain questions across large scales. Models are advancing and historically come in different types (process-based or statistical data-driven), with the recent technological advancements and integration of machine learning and hybrid process-based/statistical models. Lake ice modeling enhances our understanding of lake dynamics and allows for projections under future climate warming scenarios. To encourage the merging of technological innovation within limnological research of the less-studied winter period, we have accumulated both essential details on the history and uses of contemporary sampling, remote sensing, and modeling techniques. We crafted 100 questions in the field of winter limnology that aim to facilitate the cross-pollination of intensive and extensive modes of study to broaden knowledge of the winter period.

Water Resources Research↗

USGS2024

National-scale remotely sensed lake trophic state from 1984 through 2020

Lake trophic state is a key ecosystem property that integrates a lake’s physical, chemical, and biological processes. Despite the importance of trophic state as a gauge of lake water quality, standardized and machine-readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic state with reproducible, robust methods across time and space. We used Landsat surface reflectance data to create the first compendium of annual lake trophic state for 55,662 lakes of at least 10 ha in area throughout the contiguous United States from 1984 through 2020. The dataset was constructed with FAIR data principles (Findable, Accessible, Interoperable, and Reproducible) in mind, where data are publicly available, relational keys from parent datasets are retained, and all data wrangling and modeling routines are scripted for future reuse. Together, this resource offers critical data to address basic and applied research questions about lake water quality at a suite of spatial and temporal scales.

Scientific Data↗

USGS2024

Environmental and societal consequences of winter ice loss from lakes

More than half a billion people live near lakes that freeze over in the winter. However, lakes are rapidly losing winter ice cover in response to warming, and the rate of loss has accelerated over the past 25 years. Hampton et al . reviewed the state of seasonal ice cover on lakes and discuss some of the consequences of its disappearance. Ice loss will affect culture, economy, water quality, fisheries, and biodiversity, as well as weather and climate. —Jesse Smith

Science↗

USGS2024

The extended Global Lake area, Climate, and Population (GLCP) dataset: Extending the GLCP to include ice, snow, and radiation-related climate variables

A changing climate and increasing human population necessitate understanding global freshwater availability. To enable assessment of lake water variability from local-to-global and monthly-to-decadal scales, we extended the Global Lake area, Climate, and Population (GLCP) dataset, which contains monthly lake surface area for 1.42 million lakes with paired basin-level climate and population data from 1995 through 2020. In comparison to the previous version of the GLCP, the extended version is monthly and includes information on lake ice cover as well as basin-level snow area, humidity, longwave and shortwave radiation, and cloud cover. The extended GLCP emphasizes FAIR data principles by expanding its scripting repository and maintaining unique HydroLAKES identifiers, which enables the GLCP to be joined with other HydroLAKES-derived products. Compared to the original version, the extended GLCP contains a richer suite of variables that enable disparate analyses of lake water trends at broad spatial and temporal scales.

EarthArXiv↗

USGS2023

Inland water greenhouse gas budgets for RECCAP2: 2. Regionalization and homogenization of estimates

Inland waters are important sources of the greenhouse gasses (GHGs) carbon dioxide (CO 2 ), methane (CH 4 ) and nitrous oxide (N 2 O) to the atmosphere. In the framework of the 2 nd phase of the REgional Carbon Cycle Assessment and Processes (RECCAP-2) initiative, we synthesize existing estimates of GHG emissions from streams, rivers, lakes and reservoirs, and homogenize them with regard to underlying global maps of water surface area distribution and the effects of seasonal ice cover. We then produce regionalized estimates of GHG emissions over 10 extensive land regions. According to our synthesis, inland water GHG emissions have a global warming potential of an equivalent emission of 13.5 (9.9-20.1) and 8.3 (5.7-12.7) Pg CO 2 -eq. yr -1 at a 20 and 100 year horizon (GWP 20 and GWP 100 ), respectively. Contributions of CO 2 dominate GWP 100 , with rivers being the largest emitter. For GWP 20 , lakes and rivers are equally important emitters, and the warming potential of CH 4 is more important than that of CO 2 . Contributions from N 2 O are about two orders of magnitude lower. Normalized to the area of RECCAP-2 regions, S-America and SE-Asia show the highest emission rates, dominated by riverine CO 2 emissions.

Global Biogeochemical Cycles↗

USGS2023

Inland water greenhouse gas budgets for RECCAP2: 1. State-of-the-art of global scale assessments

Inland waters are important sources of the greenhouse gasses (GHGs) carbon dioxide (CO 2 ), methane (CH 4 ) and nitrous oxide (N 2 O) to the atmosphere. In the framework of the 2 nd phase of the REgional Carbon Cycle Assessment and Processes (RECCAP-2) initiative, we review the state of the art in estimating inland water GHG budgets at global scale, which has substantially advanced since the first phase of RECCAP nearly ten years ago. The development of increasingly sophisticated upscaling techniques, including statistical prediction and process based models, allows for spatially explicit estimates which are needed for regionalized assessments of continental GHG budgets such as those established for RECCAP. A few recent estimates also resolve the seasonal and/or interannual variability in inland water GHG emissions. Nonetheless, the global-scale assessment of inland water emissions remains challenging because of limited spatial and temporal coverage of observations and persisting uncertainties in the abundance and distribution of inland water surface areas. To decrease these uncertainties, more empirical work on the contributions of hot-spots and hot-moments to overall inland water GHG emissions is particularly needed.

Global Biogeochemical Cycles↗

USGS2023

Quantification of wetland vegetation communities features with airborne AVIRIS-NG, UAVSAR, and UAV LiDAR data in Peace-Athabasca Delta

Arctic-boreal wetlands, important ecosystems for biodiversity and ecological services, are experiencing hydrological changes including permafrost thaw, earlier snowmelt, and increased wildfire susceptibility. These changes are affecting wetland productivity, species diversity, and biogeochemical cycles. However, given the diverse forms and structures of wetland vegetation communities, traditional wetland maps generated from lower spatial and spectral resolution satellite imagery lack community-level vegetation classification and miss spatially complex patterns. In this study, we built a cloud-based workflow to map wetland vegetation community of the Peace-Athabasca Delta (PAD), Canada, by leveraging high-resolution (5-m) airborne multi-sensor datasets, namely NASA's Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), and a historical LiDAR archive. Validation of our classifications using ground references indicates that classifications derived from AVIRIS-NG have higher accuracies (≥87.9%) than either UAVSAR (65.6%) or LiDAR (75.9%) for mapping wetland vegetation communities. We also show improved classification accuracy when combining information from multiple sensors. In particular, incorporating AVIRIS-NG and UAVSAR datasets substantially reduced omission errors of wet graminoid and wet shrub classes from 29.6% to 20.5% and from 10.8% to 7.5%, respectively. Combining AVIRIS-NG and LiDAR datasets further improves overall accuracy (+2.2%) for most classifications, especially emergent vegetation, wet graminoid, and wet shrub. The best performing model, using features derived from all three sensors, achieved an overall accuracy of 93.5%. The framework established here can be used to leverage extensive airborne AVIRIS-NG and UAVSAR datasets collected across Alaska and northwest Canada to understand the spatial distribution of Arctic-Boreal wetland vegetation communities.

Remote Sensing of Environment↗

USGS2021

The ecology of river ice

Many of the world's rivers are ice-covered during winter months but increasing evidence indicates that the extent of river ice will shift substantially as winters warm. However, our knowledge of rivers during winter lags far behind that of the growing season, limiting our understanding of how ice loss will affect rivers. Physical, chemical, and biological processes change from headwaters to large rivers; thus, we expect ice processes and resulting effects on the ecology of rivers could also vary with river size, as a result of the associated changes in geomorphology, temperature regimes, and connectivity. To conceptualize these relationships, we review typically disparate literature on ice processes and winter ecology and compare what is known in the smallest and largest rivers. In doing so, we show that our ability to link ice with ecology across river networks is made difficult by a primary focus on ice processes in larger rivers and a lack of study of ecosystem processes during winter. To address some of these gaps, we provide new scenarios of river ice loss and analyses of how the annual importance of winter gross primary productivity (GPP) varies with river size. We show projected ice loss varied with large-scale watershed characteristics such as north-south orientation and that the importance of winter to annual GPP was greatest in the smallest rivers. Finally, we highlight information needed to fill knowledge gaps on winter across river networks and improve our understanding of how rivers may change as climate and ice regimes shift.

JGR Biogeosciences↗

USGS2021

The AEMON-J “Hacking Limnology” workshop series & virtual summit: Incorporating data science and open science in aquatic research

Following the 2020 “Virtual Summit: Incorporating Data Science and Open Science in Aquatic Research” (DSOS; Meyer and Zwart 2020 ), a grassroots group of scientists convened the 2nd Virtual DSOS Summit on 22–23 July 2021. DSOS combined forces with the Aquatic Ecosystem MOdeling Network - Junior (AEMON-J; https://github.com/aemon-j) to host a 4-d “Hacking Limnology” Workshop Series prior to the summit (13–16 July 2021). The aim was to focus more deeply on skill development and networking among early career researchers (ECRs), both of which are key to growing a workforce of data-intensive aquatic scientists (López Moreira M et al. in press; Meyer et al. 2021 a ). To support ECRs further, we hosted a virtual job board, where participants could note if they were either looking for employment or hiring for a position. Like the 2020 summit, there was high enthusiasm for both the summit and the workshops. In total, 686 people from over 50 countries registered for the AEMON-J Workshop Series and the DSOS Summit. Countries with the highest number of registrants included the United States (41%), Nigeria (20%), Canada (6%), Brazil (6%), and Germany (5%) (Fig. 1). To increase accessibility, there were no registration costs for the workshops and summit, and we centralized introductory training materials, coding scripts, and presentation recordings in one community website (https://aquaticdatasciopensci.github.io/; Fig. 2), which we hope will continue to support the AEMON-J and DSOS communities over time.

Limnology and Oceanography Bulletin↗

USGS2020

Integrating perspectives to understand lake ice dynamics in a changing world

Ice cover plays a critical role in physical, biogeochemical, and ecological processes in lakes. Despite its importance, winter limnology remains relatively understudied. Here, we provide a primer on the predominant drivers of freshwater lake ice cover and the current methodologies used to study lake ice, including in situ and remote sensing observations, physical based models, and experiments. We highlight opportunities for future research by integrating these four disciplines to address key knowledge gaps in our understanding of lake ice dynamics in changing winters. Advances in technology, data integration, and interdisciplinary collaboration will allow the field to move toward developing global forecasts of lake ice cover for small to large lakes across broad spatial and temporal scales, quantifying ice quality and ice thickness, moving from binary to continuous ice records, and determining how winter ice conditions and quality impact ecosystem processes in lakes over winter. Ultimately, integrating disciplines will improve our ability to understand the impacts of changing winters on lake ice.

Journal of Geophysical Research: Biogeosciences↗

USGS2016

Fluid spatial dynamics of West Nile virus in the USA: Rapid spread in a permissive host environment

The introduction of West Nile virus (WNV) into North America in 1999 is a classical example of viral emergence in a new environment, with its subsequent dispersion across the continent having a major impact on local bird populations. Despite the importance of this epizootic, the pattern, dynamics and determinants of WNV spread in its natural hosts remain uncertain. In particular, it is unclear whether the virus encountered major barriers to transmission, or spread in an unconstrained manner, and if specific viral lineages were favored over others indicative of intrinsic differences in fitness. To address these key questions in WNV evolution and ecology we sequenced the complete genomes of approximately 300 avian isolates sampled across the USA between 2001-2012. Phylogenetic analysis revealed a relatively ‘star-like' tree structure, indicative of explosive viral spread in US, although with some replacement of viral genotypes through time. These data are striking in that viral sequences exhibit relatively limited clustering according to geographic region, particularly for those viruses sampled from birds, and no strong phylogenetic association with well sampled avian species. The genome sequence data analysed here also contain relatively little evidence for adaptive evolution, particularly on structural proteins, suggesting that most viral lineages are of similar fitness, and that WNV is well adapted to the ecology of mosquito vectors and diverse avian hosts in the USA. In sum, the molecular evolution of WNV in North America depicts a largely unfettered expansion within a permissive host and geographic population with little evidence of major adaptive barriers.

Journal of Virology↗