Optimizing sampling effort and information content of biodiversity surveys: a case study of alpine grassland

Aims: Current rates of biodiversity loss do not allow for inefficient monitoring. Optimized monitoring maximizes the ratio between information and sampling effort (i.e., time and costs). Sampling effort increases with the number and size of sampling units. We hypothesize that an optimal size and number of sampling units can be determined providing maximal information via minimal effort. We apply an approach that identifies the optimal size and number of sampling quadrats. The approach can be adapted to any study system. Here we focus on alpine grassland, a diverse but threatened ecosystem. Location: Gran Paradiso National Park, Italy. Methods: We sampled nine 20 m 7 20 m-plots. Each plot consisted of 100 2 m 7 2 m-subplots. Species richness and Shannon diversity were quantified for different sizes and quantities of subplots. We simulated larger subplot sizes by unifying adjacent 2 m 7 2 m-subplots. Shannon's information entropy was used to quantify information content among richness and diversity values resulting from different subplot sizes and quantities. The optimal size and number of subplots is the lowest size and number of subplots returning maximal information. This optimal subplot size and number was determined by Mood's median test and segmented linear regression, respectively. Results: The information content among richness values increased with subplot size, irrespective of the number of subplots. Therefore, the largest subplot size available is the optimal size for information about richness. Information content among diversity values increased with subplot size if 18 or less subplots were considered, and decreased if at least 27 subplots were sampled. The subplot quantity consequently determined whether the smallest or largest subplot size available is the optimal size, and whether the optimal size can be generalized across richness and diversity. Given a 2 m 7 2 m size, we estimated an optimal quantity of 54. Given a size of 4 m 7 4 m, we estimated an optimal number of 36. The optimal number of plots can be generalized across both indices because it barely differed between the indices given a fixed subplot size. Conclusions: The information content among richness and diversity values depends on the sampling scale. Shannon's information entropy can be used to identify the optimal number and size of plots that return most information with least sampling effort. Our approach can be adapted to other study systems to create an efficient in-situ sampling design, which improves biodiversity monitoring and conservation under rapid environmental change

Data on alpine grassland diversity in Gran Paradiso National Park, Italy

The diversity of alpine grassland species and their functional traits constitute alpine ecosystem functioning and services that support human-wellbeing. However, alpine grassland diversity is threatened by land use and climate change. Field surveys and monitoring are necessary to understand and preserve such endangered ecosystems. Here we describe data on abundances (percentage cover) of 247 alpine plant species (including mosses and lichens) inside nine 20 m by 20 m plots that were subdivided into 2 m by 2 m subplots. The nine plots are located in Gran Paradiso National Park, Italy. They cover three distinct alpine vegetation subtypes (\u2018pure\u2019 natural grassland, sparsely vegetated \u2018rocky\u2019 grassland, and wetland) in each of three valleys (Bardoney, Colle de Nivolet and Levionaz) between 2200 and 2700 m a.s.l., i.e. above the treeline. The vegetation survey was conducted in 2015 at the peak of vegetation development during August. The dataset is provided as supplementary material and associated with the research article \u201cOptimizing sampling effort and information content of biodiversity surveys: a case study of alpine grassland\u201d [1]. See [1] for data interpretation

Measurement of the azimuthal anisotropy of Y(1S) and Y(2S) mesons in PbPb collisions at √S^{S}NN = 5.02 TeV

The second-order Fourier coefficients (υ$_{2}$) characterizing the azimuthal distributions of Υ(1S) and Υ(2S) mesons produced in PbPb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV are studied. The Υmesons are reconstructed in their dimuon decay channel, as measured by the CMS detector. The collected data set corresponds to an integrated luminosity of 1.7 nb$^{-1}$. The scalar product method is used to extract the υ$_{2}$ coefficients of the azimuthal distributions. Results are reported for the rapidity range |y| < 2.4, in the transverse momentum interval 0 < p$_{T}$ < 50 GeV/c, and in three centrality ranges of 10–30%, 30–50% and 50–90%. In contrast to the J/ψ mesons, the measured υ$_{2}$ values for the Υ mesons are found to be consistent with zero

Measurement of prompt D0^{0} and D‾\overline{D}0^{0} meson azimuthal anisotropy and search for strong electric fields in PbPb collisions at root SNN\sqrt{S_{NN}} = 5.02 TeV

The strong Coulomb field created in ultrarelativistic heavy ion collisions is expected to produce a rapiditydependent difference (Av2) in the second Fourier coefficient of the azimuthal distribution (elliptic flow, v2) between D0 (uc) and D0 (uc) mesons. Motivated by the search for evidence of this field, the CMS detector at the LHC is used to perform the first measurement of Av2. The rapidity-averaged value is found to be (Av2) = 0.001 ? 0.001 (stat)? 0.003 (syst) in PbPb collisions at ?sNN = 5.02 TeV. In addition, the influence of the collision geometry is explored by measuring the D0 and D0mesons v2 and triangular flow coefficient (v3) as functions of rapidity, transverse momentum (pT), and event centrality (a measure of the overlap of the two Pb nuclei). A clear centrality dependence of prompt D0 meson v2 values is observed, while the v3 is largely independent of centrality. These trends are consistent with expectations of flow driven by the initial-state geometry. ? 2021 The Author. Published by Elsevier B.V. This is an open access article under the CC BY licens

Performance of reconstruction and identification of τ leptons decaying to hadrons and vτ in pp collisions at √s=13 TeV

The algorithm developed by the CMS Collaboration to reconstruct and identify τ leptons produced in proton-proton collisions at √s=7 and 8 TeV, via their decays to hadrons and a neutrino, has been significantly improved. The changes include a revised reconstruction of π⁰ candidates, and improvements in multivariate discriminants to separate τ leptons from jets and electrons. The algorithm is extended to reconstruct τ leptons in highly Lorentz-boosted pair production, and in the high-level trigger. The performance of the algorithm is studied using proton-proton collisions recorded during 2016 at √s=13 TeV, corresponding to an integrated luminosity of 35.9 fb¯¹. The performance is evaluated in terms of the efficiency for a genuine τ lepton to pass the identification criteria and of the probabilities for jets, electrons, and muons to be misidentified as τ leptons. The results are found to be very close to those expected from Monte Carlo simulation

Performance of the CMS Level-1 trigger in proton-proton collisions at √s = 13 TeV

At the start of Run 2 in 2015, the LHC delivered proton-proton collisions at a center-of-mass energy of 13\TeV. During Run 2 (years 2015–2018) the LHC eventually reached a luminosity of 2.1× 10$^{34}$ cm$^{-2}$s$^{-1}$, almost three times that reached during Run 1 (2009–2013) and a factor of two larger than the LHC design value, leading to events with up to a mean of about 50 simultaneous inelastic proton-proton collisions per bunch crossing (pileup). The CMS Level-1 trigger was upgraded prior to 2016 to improve the selection of physics events in the challenging conditions posed by the second run of the LHC. This paper describes the performance of the CMS Level-1 trigger upgrade during the data taking period of 2016–2018. The upgraded trigger implements pattern recognition and boosted decision tree regression techniques for muon reconstruction, includes pileup subtraction for jets and energy sums, and incorporates pileup-dependent isolation requirements for electrons and tau leptons. In addition, the new trigger calculates high-level quantities such as the invariant mass of pairs of reconstructed particles. The upgrade reduces the trigger rate from background processes and improves the trigger efficiency for a wide variety of physics signals

Measurement of the Y(1S) pair production cross section and search for resonances decaying to Y(1S)μ⁺μ⁻ in proton-proton collisions at √s = 13 TeV

The fiducial cross section for Y(1S)pair production in proton-proton collisions at a center-of-mass energy of 13TeVin the region where both Y(1S)mesons have an absolute rapidity below 2.0 is measured to be 79 ± 11 (stat) ±6 (syst) ±3 (B)pbassuming the mesons are produced unpolarized. The last uncertainty corresponds to the uncertainty in the Y(1S)meson dimuon branching fraction. The measurement is performed in the final state with four muons using proton-proton collision data collected in 2016 by the CMS experiment at the LHC, corresponding to an integrated luminosity of 35.9fb$^{-1}$. This process serves as a standard model reference in a search for narrow resonances decaying to Y(1S)μ$^{+}$μ$^{-}$ in the same final state. Such a resonance could indicate the existence of a tetraquark that is a bound state of two bquarks and two b̅ antiquarks. The tetraquark search is performed for masses in the vicinity of four times the bottom quark mass, between 17.5 and 19.5GeV, while a generic search for other resonances is performed for masses between 16.5 and 27GeV. No significant excess of events compatible with a narrow resonance is observed in the data. Limits on the production cross section times branching fraction to four muons via an intermediate Y(1S)resonance are set as a function of the resonance mass