Data_Sheet_1_Improving spatial predictions of Eucalypt plantation growth by combining interpretable machine learning with the 3-PG model.docx

Accurate predictions of forest plantation growth provide forest managers with improved forest inventory estimates, forest valuation, and timely harvest schedules. Forest process-based models are increasingly used for quantifying current and potential productivity, yield gaps, and factors limiting growth, such as climate variability, soil characteristics, and water deficit. Improvements in the availability and resolution of spatial and temporal data combined with advancements in machine learning algorithms provide new opportunities to improve model predictions. This study shows how interpretable machine learning (ML) can be used to independently predict site soil fertility rating (FR) and incorporate these results into the 3-PG forest process-based model to accurately predict plantation growth. Four ensemble decision tree machine learning models—random forest trees, extremely randomized trees, gradient boost, and XG boost—were trained and compared using spatial cross-validation across the study area. FR predictions were estimated in relation to the influencing soil type and terrain characteristics, and interpretable ML methods were used to show how input feature permutations may relate to the soil fertility predictions. The results show the explanatory variables are similar across the selected ML models, with the strongest influencing variables being water leaching index, site aspect, and the silt and sand soil texture properties. The extremely randomized tree models showed the overall best performance, with only a small variation in performance across the four ML models. The method was applied to Eucalyptus nitens plantations covering over 63,000 ha in north-west Tasmania, Australia. The results using the predicted FR spatial grid with 3-PG show a strong correlation with observed growth for tree diameter and stand volume (R2 tree diameter at breast height = 0.97, RMSE = 0.85 m; R2 stand volume = 0.96, RMSE = 23.1 m3 ha−1) obtained from 161 permanent sample inventory plots ranging from 3 to 31 years old. This method has practical utility for other study sites to calibrate forest plantation soil fertility rating, in both the spatial and point-scale 3-PG model, where spatial data of soil characteristics are available. The derived soil fertility grid can provide valuable insights into the spatial variability of soil fertility in unknown areas.</p

Stomatal control of transpiration in the canopy of a clonal Eucalyptus grandis plantation

Predawn leaf water potential, stomatal conductance and microclimatic variables were measured on 13 sampling days from November 1995 through August 1996 to determine how environmental and physiological factors affect water use at the canopy scale in a plantation of mature clonal Eucalyptus grandis Hill ex-Maiden hybrids in the State of Espirito Santo, Brazil. The simple ”big leaf” Penman-Monteith model was used to estimate canopy transpiration. During the study period the predawn leaf water potential varied from –0.4 to –1.3 MPa, with the minimum values observed in the winter months (June and August 1996), while the average estimated values for canopy conductance and canopy transpiration fell from 17.3 to 5.8 mm s–1 and from 0.54 to 0.18 mm h–1, respectively. On the basis of all measurements, the average value of the decoupling coefficient was 0.25. During continuous soil water shortage a proportional reduction was observed in predawn leaf water potential and in daily maximum values of stomatal conductance, canopy transpiration and decoupling coefficient. The results showed that water vapour exchange in this canopy is strongly dominated by the regional vapour pressure deficit and that canopy transpiration is controlled mainly by stomatal conductance. On a seasonal basis, stomatal conductance and canopy transpiration were mainly related to predawn leaf water potential and, thus, to soil moisture and rainfall. Good results were obtained with a multiplicative empirical model that uses values of photosynthetically active radiation, vapour pressure deficit and predawn leaf water potential to estimate stomatal conductance

Measurement of the radius dependence of charged-particle jet suppression in Pb–Pb collisions at sNN=5.02\sqrt{s_{\rm NN}} = 5.02 TeV

The ALICE Collaboration reports a new differential measurement of inclusive jet suppression using pp and Pb–Pb collision data at center-of-mass energy per nucleon–nucleon collision $\sqrt{s_{\rm NN}} = 5.02$ TeV. Charged-particle jets are reconstructed using the anti-$k_{\rm T}$ algorithm with resolution parameters $R$ = 0.2, 0.3, 0.4, 0.5, and 0.6 in pp collisions and $R$ = 0.2, 0.4, 0.6 in central (0–10\%), semi-central (30–50\%), and peripheral (60–80\%) Pb–Pb collisions. The analysis uses a novel approach based on machine learning to mitigate the influence of jet background in central heavy-ion collisions, which enables measurements of inclusive jet suppression for jet $p_{\rm T} \ge 40$ GeV/$c$ in central collisions at a resolution parameter of $R$ = 0.6. This is the lowest value of jet $p_{\rm T}$ achieved for inclusive jet measurements at $R$ = 0.6 at the LHC, and is an important step for discriminating different models of jet quenching in the quark-gluon plasma. The transverse momentum spectra, nuclear modification factors, and derived cross section and nuclear modification factor ratios for different jet resolution parameters of charged-particle jets are presented and compared to model predictions. A mild dependence of the nuclear modification factor ratios on collision centrality and resolution parameter is observed. The results are compared to a variety of jet quenching models with varying levels of agreement, demonstrating the effectiveness of this observable to discriminate between models.The ALICE Collaboration reports a new differential measurement of inclusive jet suppression using pp and Pb$-$Pb collision data at center-of-mass energy per nucleon-nucleon collision $\sqrt{s_{\rm NN}} = 5.02$ TeV. Charged-particle jets are reconstructed using the anti-$k_{\rm T}$ algorithm with resolution parameters $R =$ 0.2, 0.3, 0.4, 0.5, and 0.6 in pp collisions and $R =$ 0.2, 0.4, 0.6 in central (0$-$10%), semi-central (30$-$50%), and peripheral (60$-$80%) Pb$-$Pb collisions. The analysis uses a novel approach based on machine learning to mitigate the influence of jet background in central heavy-ion collisions, which enables measurements of inclusive jet suppression for jet $p_{\rm T} \geq 40$ GeV/$c$ in central collisions at a resolution parameter of $R = 0.6$. This is the lowest value of jet $p_{\rm T}$ achieved for inclusive jet measurements at $R=0.6$ at the LHC, and is an important step for discriminating different models of jet quenching in the quark-gluon plasma. The transverse momentum spectra, nuclear modification factors, and derived cross section and nuclear modification factor ratios for different jet resolution parameters of charged-particle jets are presented and compared to model predictions. A mild dependence of the nuclear modification factor ratios on collision centrality and resolution parameter is observed. The results are compared to a variety of jet quenching models with varying levels of agreement, demonstrating the effectiveness of this observable to discriminate between models

Light (anti)nuclei production in Pb–Pb collisions at √sNN = 5.02 TeV

The measurement of the production of deuterons, tritons and 3He and their antiparticles in Pb-Pb collisions at sNN−−−√=5.02 TeV is presented in this article. The measurements are carried out at midrapidity (|y|< 0.5) as a function of collision centrality using the ALICE detector. The pT-integrated yields, the coalescence parameters and the ratios to protons and antiprotons are reported and compared with nucleosynthesis models. The comparison of these results in different collision systems at different centre-of-mass collision energies reveals a suppression of nucleus production in small systems. In the Statistical Hadronisation Model framework, this can be explained by a small correlation volume where the baryon number is conserved, as already shown in previous fluctuation analyses. However, a different size of the correlation volume is required to describe the proton yields in the same data sets. The coalescence model can describe this suppression by the fact that the wave functions of the nuclei are large and the fireball size starts to become comparable and even much smaller than the actual nucleus at low multiplicities

Measurement of inclusive J/ψ pair production cross section in pp collisions at √s = 13 Te

The production cross section of inclusive J/ψ pairs in pp collisions at a centre-of-mass energy s√=13 TeV is measured with ALICE. The measurement is performed for J/ψ in the rapidity interval 2.50. The production cross section of inclusive J/ψ pairs is reported to be 10.3±2.3(stat.)±1.3(syst.) nb in this kinematic interval. The contribution from non-prompt J/ψ (i.e. originated from beauty-hadron decays) to the inclusive sample is evaluated. The effective double-parton scattering cross section is computed, neglecting the single-parton scattering contribution

Energy dependence of coherent photonuclear production of J/ψ mesons in ultra-peripheral Pb-Pb collisions at sNN \sqrt{{\textrm{s}}_{\textrm{NN}}} = 5.02 TeV

International audienceThe cross section for coherent photonuclear production of J/ψ is presented as a function of the electromagnetic dissociation (EMD) of Pb. The measurement is performed with the ALICE detector in ultra-peripheral Pb-Pb collisions at a centre-of-mass energy per nucleon pair of $\sqrt{{\textrm{s}}_{\textrm{NN}}}$ = 5.02 TeV. Cross sections are presented in five different J/ψ rapidity ranges within |y| < 4, with the J/ψ reconstructed via its dilepton decay channels. In some events the J/ψ is not accompanied by EMD, while other events do produce neutrons from EMD at beam rapidities either in one or the other beam direction, or in both. The cross sections in a given rapidity range and for different configurations of neutrons from EMD allow for the extraction of the energy dependence of this process in the range 17 < W$_{γ Pb,n}$ < 920 GeV, where W$_{γ Pb,n}$ is the centre-of-mass energy per nucleon of the γPb system. This range corresponds to a Bjorken-x interval spanning about three orders of magnitude: 1.1 × 10$^{−5}$ < x < 3.3 × 10$^{−2}$. In addition to the ultra-peripheral and photonuclear cross sections, the nuclear suppression factor is obtained. These measurements point to a strong depletion of the gluon distribution in Pb nuclei over a broad, previously unexplored, energy range. These results, together with previous ALICE measurements, provide unprecedented information to probe quantum chromodynamics at high energies.[graphic not available: see fulltext

Enhanced deuteron coalescence probability in jets

The transverse-momentum (pT) spectra and coalescence parameters B2 of (anti)deuterons are measured in pp collisions at s√=13 TeV for the first time in and out of jets. In this measurement, the direction of the leading particle with the highest pT in the event (pleadT>5 GeV/c) is used as an approximation for the jet axis. The event is consequently divided into three azimuthal regions and the jet signal is obtained as the difference between the Toward region, that contains jet fragmentation products in addition to the underlying event (UE), and the Transverse region, which is dominated by the UE. The coalescence parameter in the jet is found to be approximately a factor of 10 larger than that in the underlying event. This experimental observation is consistent with the coalescence picture and can be attributed to the smaller average phase-space distance between nucleons inside the jet cone as compared to the underlying event. The results presented in this Letter are compared to predictions from a simple nucleon coalescence model, where the phase space distributions of nucleons are generated using PYTHIA 8 with the Monash 2013 tuning, and to predictions from a deuteron production model based on ordinary nuclear reactions with parametrized energy-dependent cross sections tuned on data. The latter model is implemented in PYTHIA 8.3. Both models reproduce the observed large difference between in-jet and out-of-jet coalescence parameters, although the almost flat trend of the BJet2 is not reproduced by the models, which instead give a decreasing trend