Conserving Soil and Water with Sustainable Cropping Systems

Abstract: Soils of the semiarid Canadian prairies have been subjected to substantial degradation since the native grasslands were first cultivated some 120 years ago. The degradation resulted from the combined effects of soil erosion, loss of soil organic matter (SOM), nutrient export by crops, and salinization. These soil damaging processes are the legacies of intensive tillage, monoculture cropping, and overuse of summerfallow. Long-and short-term crop rotation and soil management studies, conducted in southwest Saskatchewan, have shown the great benefits of reducing summerfallow frequency and intensity of mechanical tillage, and of using crop diversification to halt or reverse soil degradation. Nitrate leaching below the rooting depth (120 cm) after over years of continuous wheat (Triticum aestivum L.) cropping was lower than that in cropping systems that included summerfallow every 2 or 3 years. Inclusion of annual pulses, such as lentil (Lens culinaris Medikus), further reduced nitrate leaching, and increased wheat grain protein concentration in 2 of every 3 years compared to wheat monoculture grown annually. Furthermore, inclusion of the pulse crop in the rotation increased soil microbial biomass by 45% to 75%, and increased SOM by 1.8 Mg ha -1 as compared to wheat monoculture. Populations of rhizobia in the rhizosphere and rhizoplane of wheat roots were many thousand-to million-fold higher when grown in rotation with lentil than in monoculture. Shorter-term crop sequence studies have shown that the judicious selection of crop species and varieties arranged in appropriate sequences increases water and nutrient use efficiency by as much as 10% to 30%, decreases weed and disease pressure, and increases cereal grain yields by 5% to 15% and protein concentration by 6% to 16% at the systems level. Our research findings have assisted Canadian producers in identifying cropping systems that produce safe and nutritious food in an economically viable fashion, while conserving or enhancing soil and environmental quality

Comparison of Statistical Population Reconstruction Using Full and Pooled Adult Age-Class Data

BACKGROUND: Age-at-harvest data are among the most commonly collected, yet neglected, demographic data gathered by wildlife agencies. Statistical population construction techniques can use this information to estimate the abundance of wild populations over wide geographic areas and concurrently estimate recruitment, harvest, and natural survival rates. Although current reconstruction techniques use full age-class data (0.5, 1.5, 2.5, 3.5, … years), it is not always possible to determine an animal's age due to inaccuracy of the methods, expense, and logistics of sample collection. The ability to inventory wild populations would be greatly expanded if pooled adult age-class data (e.g., 0.5, 1.5, 2.5+ years) could be successfully used in statistical population reconstruction. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the performance of statistical population reconstruction models developed to analyze full age-class and pooled adult age-class data. We performed Monte Carlo simulations using a stochastic version of a Leslie matrix model, which generated data over a wide range of abundance levels, harvest rates, and natural survival probabilities, representing medium-to-big game species. Results of full age-class and pooled adult age-class population reconstructions were compared for accuracy and precision. No discernible difference in accuracy was detected, but precision was slightly reduced when using the pooled adult age-class reconstruction. On average, the coefficient of variation (i.e., SE(θ)/θ) increased by 0.059 when the adult age-class data were pooled prior to analyses. The analyses and maximum likelihood model for pooled adult age-class reconstruction are illustrated for a black-tailed deer (Odocoileus hemionus) population in Washington State. CONCLUSIONS/SIGNIFICANCE: Inventorying wild populations is one of the greatest challenges of wildlife agencies. These new statistical population reconstruction models should expand the demographic capabilities of wildlife agencies that have already collected pooled adult age-class data or are seeking a cost-effective method for monitoring the status and trends of our wild resources

Prospects for γ-ray observations of the Perseus galaxy cluster with the Cherenkov Telescope Array

Galaxy clusters are expected to be both dark matter (DM) reservoirs and storage rooms for the cosmic-ray protons (CRp) that accumulate along the cluster’s formation history. Accordingly, they are excellent targets to search for signals of DM annihilation and decay at γ-ray energies and are predicted to be sources of large-scale γ-ray emission due to hadronic interactions in the intracluster medium (ICM). In this paper, we estimate the sensitivity of the Cherenkov Telescope Array (CTA) to detect diffuse γ-ray emission from the Perseus galaxy cluster. We first perform a detailed spatial and spectral modelling of the expected signal for both the DM and the CRp components. For each case, we compute the expected CTA sensitivity accounting for the CTA instrument response functions. The CTA observing strategy of the Perseus cluster is also discussed. In the absence of a diffuse signal (non-detection), CTA should constrain the CRp to thermal energy ratio X500 within the characteristic radius R500 down to about X500 < 3 × 10−3, for a spatial CRp distribution that follows the thermal gas and a CRp spectral index αCRp = 2.3. Under the optimistic assumption of a pure hadronic origin of the Perseus radio mini-halo and depending on the assumed magnetic field profile, CTA should measure αCRp down to about ∆αCRp ≃ 0.1 and the CRp spatial distribution with 10% precision, respectively. Regarding DM, CTA should improve the current ground-based γ-ray DM limits from clusters observations on the velocity-averaged annihilation cross-section by a factor of up to ∼ 5, depending on the modelling of DM halo substructure. In the case of decay of DM particles, CTA will explore a new region of the parameter space, reaching models with τχ > 1027 s for DM masses above 1 TeV. These constraints will provide unprecedented sensitivity to the physics of both CRp acceleration and transport at cluster scale and to TeV DM particle models, especially in the decay scenario

Prospects for γ-ray observations of the Perseus galaxy cluster with the Cherenkov Telescope Array

Galaxy clusters are expected to be dark matter (DM) reservoirs and storage rooms for the cosmic-ray protons (CRp) that accumulate along the cluster's formation history. Accordingly, they are excellent targets to search for signals of DM annihilation and decay at gamma-ray energies and are predicted to be sources of large-scale gamma-ray emission due to hadronic interactions in the intracluster medium. We estimate the sensitivity of the Cherenkov Telescope Array (CTA) to detect diffuse gamma-ray emission from the Perseus galaxy cluster. We perform a detailed spatial and spectral modelling of the expected signal for the DM and the CRp components. For each, we compute the expected CTA sensitivity. The observing strategy of Perseus is also discussed. In the absence of a diffuse signal (non-detection), CTA should constrain the CRp to thermal energy ratio within the radius $R_{500}$ down to about X_{500}<3\times 10^{-3}, for a spatial CRp distribution that follows the thermal gas and a CRp spectral index $α_{\rm CRp}=2.3$. Under the optimistic assumption of a pure hadronic origin of the Perseus radio mini-halo and depending on the assumed magnetic field profile, CTA should measure $α_{\rm CRp}$ down to about $Δα_{\rm CRp}\simeq 0.1$ and the CRp spatial distribution with 10% precision. Regarding DM, CTA should improve the current ground-based gamma-ray DM limits from clusters observations on the velocity-averaged annihilation cross-section by a factor of up to $\sim 5$, depending on the modelling of DM halo substructure. In the case of decay of DM particles, CTA will explore a new region of the parameter space, reaching models with τ_χ>10^{27}s for DM masses above 1 TeV. These constraints will provide unprecedented sensitivity to the physics of both CRp acceleration and transport at cluster scale and to TeV DM particle models, especially in the decay scenario

Ctapipe - Prototype Open Event Reconstruction Pipeline for the Cherenkov Telescope Array

The Cherenkov Telescope Array Observatory (CTAO) is the next-generation ground-based gamma-ray observatory currently under construction. It will improve over the current generation of imaging atmospheric Cherenkov telescopes (IACTs) by a factor of five to ten in sensitivity and it will be able to observe the whole sky from a combination of two sites: a northern site in La Palma, Spain, and a southern one in Paranal, Chile. CTAO will also be the first open ground-based gamma-ray observatory. Accordingly, the CTAO data processing pipeline is developed as open-source software and ctapipe will be a core package therein. The event reconstruction pipeline accepts raw data of the telescopes and processes it to produce suitable input for the higher-level science tools. Its primary tasks include reconstructing the physical properties of each recorded air shower and providing the corresponding instrument response functions. ctapipe is a python framework providing algorithms and command-line tools to facilitate raw data calibration, image extraction, image parametrization and event reconstruction. Its current main focus is the analysis of simulated data but it has also been successfully applied for the analysis of data obtained with the CTA prototype telescopes, and first science results have now been obtained by the LST-1 collaboration using ctapipe. A plugin system also allows the processing of nonCTA data. Recent updates, including event reconstruction using machine learning and a new plugin system as well as the roadmap towards a 1.0 release will be presented

Event reconstruction using pattern spectra and convolutional neural networks for the Cherenkov Telescope Array

The Cherenkov Telescope Array (CTA) is the future observatory for ground-based imaging atmospheric Cherenkov telescopes. Each telescope will provide a snapshot of gamma-ray induced particle showers by capturing the induced Cherenkov emission at ground level. The simulation of such events provides camera images that can be used as training data for convolutional neural networks (CNNs) to differentiate signals from background events and to determine the energy of the initial gamma-ray events. Pattern spectra are commonly used tools for image classification and provide the distributions of the sizes and shapes of features comprising an image. The application of pattern spectra on a CNN allows the selection of relevant combinations of features within an image. In this work, we generate pattern spectra from simulated gamma-ray images to train a CNN for signal-background separation and energy reconstruction for CTA. We compare our results to a CNN trained with CTA images and find that the pattern spectra-based analysis is computationally less expensive but not competitive with the purely CTA images-based analysis. Thus, we conclude that the CNN must rely on additional features in the CTA images not captured by the pattern spectra

Multiwavelength study of the galactic PeVatron candidate LHAASO J2108+5157

Context. Several new ultrahigh-energy (UHE) γ-ray sources have recently been discovered by the Large High Altitude Air Shower Observatory (LHAASO) collaboration. These represent a step forward in the search for the so-called Galactic PeVatrons, the enigmatic sources of the Galactic cosmic rays up to PeV energies. However, it has been shown that multi-TeV γ-ray emission does not necessarily prove the existence of a hadronic accelerator in the source; indeed this emission could also be explained as inverse Compton scattering from electrons in a radiation-dominated environment. A clear distinction between the two major emission mechanisms would only be made possible by taking into account multi-wavelength data and detailed morphology of the source. Aims. We aim to understand the nature of the unidentified source LHAASO J2108+5157, which is one of the few known UHE sources with no very high-energy (VHE) counterpart. Methods. We observed LHAASO J2108+5157 in the X-ray band with XMM-Newton in 2021 for a total of 3.8 hours and at TeV energies with the Large-Sized Telescope prototype (LST-1), yielding 49 hours of good-quality data. In addition, we analyzed 12 years of Fermi-LAT data, to better constrain emission of its high-energy (HE) counterpart 4FGL J2108.0+5155. We used naima and jetset software packages to examine the leptonic and hadronic scenario of the multi-wavelength emission of the source. Results. We found an excess (3.7σ) in the LST-1 data at energies E &gt; 3 TeV. Further analysis of the whole LST-1 energy range, assuming a point-like source, resulted in a hint (2.2σ) of hard emission, which can be described with a single power law with a photon index of Σ = 1.6 ± 0.2 the range of 0.3 - 100 TeV. We did not find any significant extended emission that could be related to a supernova remnant (SNR) or pulsar wind nebula (PWN) in the XMM-Newton data, which puts strong constraints on possible synchrotron emission of relativistic electrons. We revealed a new potential hard source in Fermi-LAT data with a significance of 4σ and a photon index of Σ = 1.9 ± 0.2, which is not spatially correlated with LHAASO J2108+5157, but including it in the source model we were able to improve spectral representation of the HE counterpart 4FGL J2108.0+5155. Conclusions. The LST-1 and LHAASO observations can be explained as inverse Compton-dominated leptonic emission of relativistic electrons with a cutoff energy of 100-30+70 TeV. The low magnetic field in the source imposed by the X-ray upper limits on synchrotron emission is compatible with a hypothesis of a PWN or a TeV halo. Furthermore, the spectral properties of the HE counterpart are consistent with a Geminga-like pulsar, which would be able to power the VHE-UHE emission. Nevertheless, the lack of a pulsar in the neighborhood of the UHE source is a challenge to the PWN/TeV-halo scenario. The UHE γ rays can also be explained as π0 decay-dominated hadronic emission due to interaction of relativistic protons with one of the two known molecular clouds in the direction of the source. Indeed, the hard spectrum in the LST-1 band is compatible with protons escaping a shock around a middle-aged SNR because of their high low-energy cut-off, but the origin of the HE γ-ray emission remains an open question

Observations of the Crab Nebula and Pulsar with the Large-sized Telescope Prototype of the Cherenkov Telescope Array

The Cherenkov Telescope Array (CTA) is a next-generation ground-based observatory for gamma-ray astronomy at very high energies. The Large-Sized Telescope prototype (LST-1) is located at the CTA-North site, on the Canary Island of La Palma. LSTs are designed to provide optimal performance in the lowest part of the energy range covered by CTA, down to ≃20 GeV. LST-1 started performing astronomical observations in 2019 November, during its commissioning phase, and it has been taking data ever since. We present the first LST-1 observations of the Crab Nebula, the standard candle of very-high-energy gamma-ray astronomy, and use them, together with simulations, to assess the performance of the telescope. LST-1 has reached the expected performance during its commissioning period—only a minor adjustment of the preexisting simulations was needed to match the telescope’s behavior. The energy threshold at trigger level is around 20 GeV, rising to ≃30 GeV after data analysis. Performance parameters depend strongly on energy, and on the strength of the gamma-ray selection cuts in the analysis: angular resolution ranges from 0.°12-0.°40, and energy resolution from 15%-50%. Flux sensitivity is around 1.1% of the Crab Nebula flux above 250 GeV for a 50 hr observation (12% for 30 minutes). The spectral energy distribution (in the 0.03-30 TeV range) and the light curve obtained for the Crab Nebula agree with previous measurements, considering statistical and systematic uncertainties. A clear periodic signal is also detected from the pulsar at the center of the Nebula

Chasing Gravitational Waves with the Cherenkov Telescope Array

The detection of gravitational waves (GWs) from a binary neutron star (BNS) merger by Advanced LIGO and Advanced Virgo (GW170817), along with the discovery of the electromagnetic counterparts of this GW event, ushered in a new era of multimessenger astronomy, providing the first direct evidence that BNS mergers are progenitors of short gamma-ray bursts (GRBs). Such events may also produce very-high-energy (VHE, > 100GeV) photons which have yet to be detected in coincidence with a GW signal. The Cherenkov Telescope Array (CTA) is a next-generation VHE observatory which aims to be indispensable in this search, with an unparalleled sensitivity and ability to slew anywhere on the sky within a few tens of seconds. Achieving such a feat will require a comprehensive real-time strategy capable of coordinating searches over potentially very large regions of the sky. This work will evaluate and provide estimations on the number of GW-CTA events determined from simulated BNS systems and short GRBs, considering both on- and off-axis emission. In addition, we will present and discuss the prospects of potential follow-up strategies with CTA