Improving the estimation of deep-sea megabenthos biomass: dimension to wet weight conversions for abyssal invertebrates

Deep-sea megafaunal biomass has typically been assessed by sampling with benthic sledges and trawls, but non-destructive methods, particularly photography, are becoming increasingly common. Estimation of individual wet weight in seabed photographs has been achieved using equations obtained from measured trawl-caught specimens for a limited number of taxa. However, a lack of appropriate conversion factors has limited estimation across taxa encompassing whole communities. Here we compile relationships between measured body dimensions and preserved wet weights for a comprehensive catalogue of abyssal epibenthic megafauna, using ~47,000 specimens from the Porcupine Abyssal Plain (NE Atlantic) housed in the Discovery Collections. The practical application of the method is demonstrated using an extremely large dataset of specimen measurements from seabed photographs taken in the same location. We also collate corresponding field data on fresh wet weight, to estimate the impact of fixation in formalin and preservation in industrial denatured alcohol on the apparent biomass. Taxa with substantial proportions of soft tissues lose 35 to 60% of their wet weight during preservation, while those with greater proportions of hard tissues lose 10 to 20%. Our total estimated fresh wet weight biomass of holothurians and cnidarians in the photographic survey was ~20 times the previous estimates of total invertebrate biomass based on trawl catches. This dramatic uplift in megabenthic biomass has significant implications for studies of standing stocks, community metabolism, and numerical modelling of benthic carbon flows

Space‐Scale Resolved Surface Fluxes Across a Heterogeneous, Mid‐Latitude Forested Landscape

The Earth\u27s surface is heterogeneous at multiple scales owing to spatial variability in various properties. The atmospheric responses to these heterogeneities through fluxes of energy, water, carbon, and other scalars are scale-dependent and nonlinear. Although these exchanges can be measured using the eddy covariance technique, widely used tower-based measurement approaches suffer from spectral losses in lower frequencies when using typical averaging times. However, spatially resolved measurements such as airborne eddy covariance measurements can detect such larger scale (meso-β, meso-γ) transport. To evaluate the prevalence and magnitude of these flux contributions, we applied wavelet analysis to airborne flux measurements over a heterogeneous mid-latitude forested landscape, interspersed with open water bodies and wetlands. The measurements were made during the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors intensive field campaign. We ask, how do spatial scales of surface-atmosphere fluxes vary over heterogeneous surfaces across the day and across seasons? Measured fluxes were separated into smaller-scale turbulent and larger-scale mesoscale contributions. We found significant mesoscale contributions to sensible and latent heat fluxes through summer to autumn which would not be resolved in single-point tower measurements through traditional time-domain half-hourly Reynolds decomposition. We report scale-resolved flux transitions associated with seasonal and diurnal changes of the heterogeneous study domain. This study adds to our understanding of surface-atmospheric interactions over unstructured heterogeneities and can help inform multi-scale model-data integration of weather and climate models at a sub-grid scale

Novel approach to observing system simulation experiments improves information gain of surface-atmosphere field measurements

The observing system design of multidisciplinary field measurements involves a variety of considerations on logistics, safety, and science objectives. Typically, this is done based on investigator intuition and designs of prior field measurements. However, there is potential for considerable increases in efficiency, safety, and scientific success by integrating numerical simulations in the design process. Here, we present a novel numerical simulation-environmental response function (NS-ERF) approach to observing system simulation experiments that aids surface-atmosphere synthesis at the interface of mesoscale and microscale meteorology. In a case study we demonstrate application of the NS-ERF approach to optimize the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19). During CHEESEHEAD19 pre-field simulation experiments, we considered the placement of 20 eddy covariance flux towers, operations for 72h of low-altitude flux aircraft measurements, and integration of various remote sensing data products. A 2h high-resolution large eddy simulation created a cloud-free virtual atmosphere for surface and meteorological conditions characteristic of the field campaign domain and period. To explore two specific design hypotheses we super-sampled this virtual atmosphere as observed by 13 different yet simultaneous observing system designs consisting of virtual ground, airborne, and satellite observations. We then analyzed these virtual observations through ERFs to yield an optimal aircraft flight strategy for augmenting a stratified random flux tower network in combination with satellite retrievals. We demonstrate how the novel NS-ERF approach doubled CHEESEHEAD19's potential to explore energy balance closure and spatial patterning science objectives while substantially simplifying logistics. Owing to its modular extensibility, NS-ERF lends itself to optimizing observing system designs also for natural climate solutions, emission inventory validation, urban air quality, industry leak detection, and multi-species applications, among other use cases. © 2021 Stefan Metzger et al

Retrieval of atmospheric attenuation using combined ground-based and airborne 95-GHz cloud radar measurements

Includes bibliographical references (page 1353).Cloud measurements at millimeter-wave frequencies are affected by attenuation due to atmospheric gases, clouds, and precipitation. Estimation of the true equivalent radar reflectivity, Ze, is complicated because extinction mechanisms are not well characterized at these short wavelengths. This paper discusses cloud radar calibration and intercomparison of airborne and ground-based radar measurements and presents a unique algorithm for attenuation retrieval. This algorithm is based on dual 95-GHz radar measurements of the same cloud and precipitation volumes collected from opposing viewing angles. True radar reflectivity is retrieved by combining upward-looking and downward-looking radar profiles. This method reduces the uncertainty in radar reflectivity and attenuation estimates, since it does not require a priori knowledge of hydrometeors' microphysical properties. Results from this technique are compared with results retrieved from the Hitschfeld and Bordan algorithm, which uses single-radar measurements with path-integrated attenuation as a constraint. Further analysis is planned to employ this dual-radar algorithm in order to refine single-radar attenuation retrieval techniques, which will be used by operational sensors such as the CloudSat radar

Eddy covariance measurements highlight sources of nitrogen oxide emissions missing from inventories for central London

During March–June 2017 emissions of nitrogen oxides were measured via eddy covariance at the British Telecom Tower in central London, UK. Through the use of a footprint model the expected emissions were simulated from the spatially resolved National Atmospheric Emissions Inventory for 2017 and compared with the measured emissions. These simulated emissions were shown to underestimate measured emissions during the daytime by a factor of 1.48, but they agreed well overnight. Furthermore, underestimations were spatially mapped, and the areas around the measurement site responsible for differences in measured and simulated emissions were inferred. It was observed that areas of higher traffic, such as major roads near national rail stations, showed the greatest underestimation by the simulated emissions. These discrepancies are partially attributed to a combination of the inventory not fully capturing traffic conditions in central London and both the spatial and temporal resolution of the inventory not fully describing the high heterogeneity of the urban centre. Understanding of this underestimation may be further improved with longer measurement time series to better understand temporal variation and improved temporal scaling factors to better simulate sub-annual emissions

Global Precipitation Measurement Cold Season Precipitation Experiment (GCPEx): For Measurement Sake Let it Snow

As a component of the Earth's hydrologic cycle, and especially at higher latitudes,falling snow creates snow pack accumulation that in turn provides a large proportion of the fresh water resources required by many communities throughout the world. To assess the relationships between remotely sensed snow measurements with in situ measurements, a winter field project, termed the Global Precipitation Measurement (GPM) mission Cold Season Precipitation Experiment (GCPEx), was carried out in the winter of 2011-2012 in Ontario, Canada. Its goal was to provide information on the precipitation microphysics and processes associated with cold season precipitation to support GPM snowfall retrieval algorithms that make use of a dual-frequency precipitation radar and a passive microwave imager on board the GPM core satellite,and radiometers on constellation member satellites. Multi-parameter methods are required to be able to relate changes in the microphysical character of the snow to measureable parameters from which precipitation detection and estimation can be based. The data collection strategy was coordinated, stacked, high-altitude and in-situ cloud aircraft missions with three research aircraft sampling within a broader surface network of five ground sites taking in-situ and volumetric observations. During the field campaign 25 events were identified and classified according to their varied precipitation type, synoptic context, and precipitation amount. Herein, the GCPEx fieldcampaign is described and three illustrative cases detailed

Connecting Land–Atmosphere Interactions to Surface Heterogeneity in CHEESEHEAD19

The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model–data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon–Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world’s highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models

Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use

Should the poultry red mite Dermanyssus gallinae be of wider concern for veterinary and medical science?

The poultry red mite Dermanyssus gallinae is best known as a threat to the laying-hen industry; adversely affecting production and hen health and welfare throughout the globe, both directly and through its role as a disease vector. Nevertheless, D. gallinae is being increasingly implemented in dermatological complaints in non-avian hosts, suggesting that its significance may extend beyond poultry. The main objective of the current work was to review the potential of D. gallinae as a wider veterinary and medical threat. Results demonstrated that, as an avian mite, D. gallinae is unsurprisingly an occasional pest of pet birds. However, research also supports that these mites will feed from a range of other animals including: cats, dogs, rodents, rabbits, horses and man. We conclude that although reported cases of D. gallinae infesting mammals are relatively rare, when coupled with the reported genetic plasticity of this species and evidence of permanent infestations on non-avian hosts, potential for host-expansion may exist. The impact of, and mechanisms and risk factors for such expansion are discussed, and suggestions for further work made. Given the potential severity of any level of host-expansion in D. gallinae, we conclude that further research should be urgently conducted to confirm the full extent of the threat posed by D. gallinae to (non-avian) veterinary and medical sectors

Phylogeny and Historical Biogeography of Asian Pterourus Butterflies (Lepidoptera: Papilionidae): A Case of Intercontinental Dispersal from North America to East Asia

The phylogenetic status of the well-known Asian butterflies often known as Agehana (a species group, often treated as a genus or a subgenus, within Papilio sensu lato) has long remained unresolved. Only two species are included, and one of them especially, Papilio maraho, is not only rare but near-threatened, being monophagous on its vulnerable hostplant, Sassafras randaiense (Lauraceae). Although the natural history and population conservation of “Agehana” has received much attention, the biogeographic origin of this group still remains enigmatic. To clarify these two questions, a total of 86 species representatives within Papilionidae were sampled, and four genes (concatenated length 3842 bp) were used to reconstruct their phylogenetic relationships and historical scenarios. Surprisingly, “Agehana” fell within the American Papilio subgenus Pterourus and not as previously suggested, phylogenetically close to the Asian Papilio subgenus Chilasa. We therefore formally synonymize Agehana with Pterourus. Dating and biogeographic analysis allow us to infer an intercontinental dispersal of an American ancestor of Asian Pterourus in the early Miocene, which was coincident with historical paleo-land bridge connections, resulting in the present “East Asia-America” disjunction distribution. We emphasize that species exchange between East Asia and America seems to be a quite frequent occurrence in butterflies during the Oligocene to Miocene climatic optima.© 2015 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited