Methane Mapping with Future Satellite Imaging Spectrometers

This study evaluates a new generation of satellite imaging spectrometers to measure point source methane emissions from anthropogenic sources. We used the Airborne Visible and Infrared Imaging Spectrometer Next Generation(AVIRIS-NG) images with known methane plumes to create two simulated satellite products. One simulation had a 30 m spatial resolution with similar to 200 Signal-to-Noise Ratio (SNR) in the Shortwave Infrared (SWIR) and the other had a 60 m spatial resolution with similar to 400 SNR in the SWIR; both products had a 7.5 nm spectral spacing. We applied a linear matched filter with a sparsity prior and an albedo correction to detect and quantify the methane emission in the original AVIRIS-NG images and in both satellite simulations. We also calculated an emission flux for all images. We found that all methane plumes were detectable in all satellite simulations. The flux calculations for the simulated satellite images correlated well with the calculated flux for the original AVIRIS-NG images. We also found that coarsening spatial resolution had the largest impact on the sensitivity of the results. These results suggest that methane detection and quantification of point sources will be possible with the next generation of satellite imaging spectrometers.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Two years of satellite-based carbon dioxide emission quantification at the world's largest coal-fired power plants

Carbon dioxide (CO2) emissions from combustion sources are uncertain in many places across the globe. Satellites have the ability to detect and quantify emissions from large CO2 point sources, including coal-fired power plants. In this study, we routinely made observations with the PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite imaging spectrometer and the Orbiting Carbon Observatory-3 (OCO-3) instrument aboard the International Space Station at over 30 coal-fired power plants between 2021 and 2022. CO2 plumes were detected in 50 % of the acquired PRISMA scenes, which is consistent with the combined influence of viewing parameters on detection (solar illumination and surface reflectance) and unknown factors (e.g., daily operational status). We compare satellite-derived emission rates to in situ stack emission observations and find average agreement to within 27 % for PRISMA and 30 % for OCO-3, although more observations are needed to robustly characterize the error. We highlight two examples of fusing PRISMA with OCO-2 and OCO-3 observations in South Africa and India. For India, we acquired PRISMA and OCO-3 observations on the same day and used the high-spatial-resolution capability of PRISMA (30 m spatial/pixel resolution) to partition relative contributions of two distinct emitting power plants to the net emission. Although an encouraging start, 2 years of observations from these satellites did not produce sufficient observations to estimate annual average emission rates within low (&lt;15 %) uncertainties. However, as the constellation of CO2-observing satellites is poised to significantly improve in the coming decade, this study offers an approach to leverage multiple observation platforms to better quantify and characterize uncertainty for large anthropogenic emission sources.</p

Double-blind validation of alternative wild bee identification techniques: DNA metabarcoding and in vivo determination in the field

Over the past few decades, several investigations around the globe have reported alarming declines in the abundance and diversity of bee species. The success of effective conservation strategies targeting these important pollinators relies heavily on accurate biodiversity assessments. The shortage of taxonomic experts and the escalation of the ongoing biodiversity crisis call for the development of alternative identification tools to implement efficient monitoring programs. The validation of such techniques is crucial to ensure that they provide results comparable to those of traditional morphotaxonomy. Here we performed two double-blind experiments to evaluate the accuracy of a pair of new techniques used for wild bee identification: DNA metabarcoding and in vivo identification in the field. The methods were tested on sets of wild bees from Germany and their results compared against evaluations done by panels of bee experts using traditional morphotaxonomy. On average the congruency of species identification between metabarcoding and morphotaxonomy was 88.98% across samples (N = 10), while in vivo identification and morphotaxonomy were 91.81% congruent (N = 7) for bees considered feasible for in vivo identification in the field. Traditional morphotaxonomy showed similar congruencies when compared to itself: 93.65% in the metabarcoding study and 92.96% in the in vivo study. Overall, these results support both new methods as viable alternatives to traditional microscopy-based assessment, with neither method being error-free. Metabarcoding provides a suitable option to analyze large numbers of specimens in the absence of highly trained taxonomic experts, while in vivo identification is recommended for repeated long-term monitoring, and when working in areas where the sampling of individuals could threaten local populations of endangered wild bee species. Further research is still needed to explore the potential of both techniques for conservation management and wildlife monitoring, as well as to overcome their current limitations as taxonomic tools

Generalization Mediates Sensitivity to Complex Odor Features in the Honeybee

Animals use odors as signals for mate, kin, and food recognition, a strategy which appears ubiquitous and successful despite the high intrinsic variability of naturally-occurring odor quantities. Stimulus generalization, or the ability to decide that two objects, though readily distinguishable, are similar enough to afford the same consequence [1], could help animals adjust to variation in odor signals without losing sensitivity to key inter-stimulus differences. The present study was designed to investigate whether an animal's ability to generalize learned associations to novel odors can be influenced by the nature of the associated outcome. We use a classical conditioning paradigm for studying olfactory learning in honeybees [2] to show that honeybees conditioned on either a fixed- or variable-proportion binary odor mixture generalize learned responses to novel proportions of the same mixture even when inter-odor differences are substantial. We also show that the resulting olfactory generalization gradients depend critically on both the nature of the stimulus-reward paradigm and the intrinsic variability of the conditioned stimulus. The reward dependency we observe must be cognitive rather than perceptual in nature, and we argue that outcome-dependent generalization is necessary for maintaining sensitivity to inter-odor differences in complex olfactory scenes

Two years of satellite-based carbon dioxide emission quantification at the world's largest coal-fired power plants

Carbon dioxide (CO2) emissions from combustion sources are uncertain in many places across the globe. Satellites have the ability to detect and quantify emissions from large CO2 point sources, including coal-fired power plants. In this study, we routinely made observations with the PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite imaging spectrometer and the Orbiting Carbon Observatory-3 (OCO-3) instrument aboard the International Space Station at over 30 coal-fired power plants between 2021 and 2022. CO2 plumes were detected in 50 % of the acquired PRISMA scenes, which is consistent with the combined influence of viewing parameters on detection (solar illumination and surface reflectance) and unknown factors (e.g., daily operational status). We compare satellite-derived emission rates to in situ stack emission observations and find average agreement to within 27 % for PRISMA and 30 % for OCO-3, although more observations are needed to robustly characterize the error. We highlight two examples of fusing PRISMA with OCO-2 and OCO-3 observations in South Africa and India. For India, we acquired PRISMA and OCO-3 observations on the same day and used the high-spatial-resolution capability of PRISMA (30 m spatial/pixel resolution) to partition relative contributions of two distinct emitting power plants to the net emission. Although an encouraging start, 2 years of observations from these satellites did not produce sufficient observations to estimate annual average emission rates within low (&lt;15 %) uncertainties. However, as the constellation of CO2-observing satellites is poised to significantly improve in the coming decade, this study offers an approach to leverage multiple observation platforms to better quantify and characterize uncertainty for large anthropogenic emission sources.</p

Drone aggregation behavior in the social wasp Vespula germanica (Hymenoptera: Vespidae): Effect of kinship and density

Inbreeding can have negative consequences on population viability because of the reduced fitness of the progeny. In general, most species have developed mechanisms to minimize inbreeding such as dispersal and kin avoidance behavior. In the eusocial Hymenoptera, related individuals typically share a common nest and have relatively short mating periods, this could lead to inbreeding, and because of their single?locus complementary sex determination system, it may generate diploid males that could result in infertile triploid progeny representing a cost for the colony. Vespula germanica, is an eusocial wasp that has invaded many parts of the world, despite likely facing a reduced genetic pool during the arrival phases. We ask whether male wasp display specific aggregation behavior that favors genetic diversity, key to reduce inbreeding. Through a set of laboratory experiments, we investigated the effects of drone nestmateship and density on the aggregation behavior of V. germanica drones. We show that drones avoid aggregating with their nestmates at all densities while non-nestmates are avoided only at high densities. This suggests that lek genetic diversity and density could be regulated through drone behavior and in the long run minimize inbreeding favoring invasion success.Fil: Masciocchi, Maité. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; ArgentinaFil: Angeletti, Bárbara. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; ArgentinaFil: Corley, Juan Carlos. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; ArgentinaFil: Martinez Von Ellrichshausen, Andres Santiago. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentin