Minority Species Research Articles

On the Replicability of the Thermodynamic Modeling of Spectroscopic Titration Data in the Nickel(II) En System

ABSTRACTCharacterizing complicated solution phase systems in situ requires advanced modeling techniques to capture the intricate balances between the many chemical species. Due to the error inherent in any scientific measurement, a spectrophotometric titration experiment with nickel(II) and ethylenediamine (en) was repeated six times using an autotitrator to test the replicability of the data and the consistency of the resulting thermodynamic model. All six datasets could be modeled very tightly (R2 > 99.9999%) with the following eight complexes: [Ni]2+, [Ni2en]4+, [Nien]2+, [Ni2en3]4+, [Nien2]2+, [Ni2en5]4+, [Nien3]2+, and [Nien6]2+. The logK values for the stepwise associative reactions agree with existing literature values for the majority species ([Nienn = 1–3]2+) and matched expectations for the minority species; 95% confidence intervals for each logK value were determined via bootstrapping, which quantifies the variability in the binding constant value that is supported by a given dataset. The repeated experiments, which could not be successfully concatenated together, demonstrate that replication is crucial to capturing all the variability in the logK values. Conversely, bootstrapped confidence intervals across multiple experiments can be readily combined to generate an appropriate range for an experimentally determined binding constant.

Tracking Minority Species in Redox Reactions: A Quantitative Combined XAS and Modulation Excitation Study.

Understanding the nature of intermediates/active species in reactions is a major challenge in chemistry. This is because spectator species typically dominate the experimentally derived data and consequently active phase contributions are masked. Transient methods offer a means to bypass this difficulty. In particular, modulation excitation with phase-sensitive detection (ME-PSD) provides a mechanism to distinguish between spectator and reacting species. Herein, modulation excitation (ME) time-resolved (energy dispersive) X-ray absorption spectroscopy, assisted by phase sensitive detection (PSD) analysis, has been applied to the study of a liquid phase process; in this case the classic ferrocyanide/ferricyanide redox couple. Periodic switches of the electrical potential (anodic/cathodic) enabled the use of the ME approach. Structural changes at fractions as low as 2 % of the total number of electroactive species were detected within the X-ray beam probe volume containing ~30 pmol of Fe(II)/Fe(III).

Tracking Minority Species in Redox Reactions: A Quantitative Combined XAS and Modulation Excitation Study

AbstractUnderstanding the nature of intermediates/active species in reactions is a major challenge in chemistry. This is because spectator species typically dominate the experimentally derived data and consequently active phase contributions are masked. Transient methods offer a means to bypass this difficulty. In particular, modulation excitation with phase‐sensitive detection (ME‐PSD) provides a mechanism to distinguish between spectator and reacting species. Herein, modulation excitation (ME) time‐resolved (energy dispersive) X‐ray absorption spectroscopy, assisted by phase sensitive detection (PSD) analysis, has been applied to the study of a liquid phase process; in this case the classic ferrocyanide/ferricyanide redox couple. Periodic switches of the electrical potential (anodic/cathodic) enabled the use of the ME approach. Structural changes at fractions as low as 2 % of the total number of electroactive species were detected within the X‐ray beam probe volume containing ~30 pmol of Fe(II)/Fe(III).

Improving Balanced Accuracy for Minority Plant Species under Data Imbalance

Regardless of the widely known success of deep learning in classification, such models are commonly measured by metrics that do not account for data imbalance, especially in terms of predictions per class, ignoring minority classes. This can be a problem, as minority classes are often the most difficult to predict and collect data for. In the plant domain, for example, species with fewer samples are often the ones that are hardest to collect and predict in the field. As we continue to identify more and more plant species, more of them become minority species, making it increasingly difficult to accurately classify them using traditional machine learning methods. To address this issue, we explore the combination of traditional data and machine learning approaches with deep learning techniques such as self-supervision in a preprocessing stage. By using self-supervised training together with different sampling algorithms and class weights, we were able to improve the balanced accuracy metric for minority plant species by between 7.9% and 13% without affecting general accuracy. This shows that using deep learning techniques in combination with traditional machine learning methods can help to improve the accuracy of predictions for minority classes, even in domains where data is limited.

Modeling of ion cyclotron resonance frequency heating of proton-boron plasmas in EHL-2 spherical tokamak

Ion cyclotron resonance heating (ICRH) stands out as a widely utilized and cost-effective auxiliary method for plasma heating, bearing significant importance in achieving high-performance discharges in p-11B plasmas. In light of the specific context of p-11B plasma in the EHL-2 device, we conducted a comprehensive scan of the fundamental physical parameters of the antenna using the full-wave simulation program TORIC. Our preliminary result indicated that for p-11B plasma, optimal ion heating parameters include a frequency of 40 MHz, with a high toroidal mode number like to heat the majority H ions. In addition, we discussed the impact of concentration of minority ion species on ion cyclotron resonance heating when 11B serves as the heavy minority species. The significant difference in charge-to-mass ratio between boron and hydrogen ions results in a considerable distance between the hybrid resonance layer and the tow inverted cyclotron resonance layer, necessitating a quite low boron ion concentration to achieve effective minority heating. We also considered another method of direct heating of hydrogen ions in the presence of boron ion minority. It is found that at appropriate boron ion concentrations ( ), the position of the hybrid resonance layer approaches that of the hydrogen ion cyclotron resonance layer, thereby altering the polarization at this position and significantly enhancing hydrogen ion fundamental absorption.

Weed species classification with UAV imagery and standard CNN models: Assessing the frontiers of training and inference phases

Accurate weed species identification is crucial for effective site-specific weed management (SSWM), enabling targeted and timely control measures for each weed in crop field. This study advanced the current approach to species-level weed identification during the early growth stage by integrating unmanned aerial vehicles (UAVs) imagery with standard convolutional neural networks (CNNs) models such as VGG16, Resnet152 and Inception-Resnet-v2. For this, a robust dataset was created with 33,467 labels of weeds (Atriplex patula, Chenopodium album, Convolvulus arvensis, Cyperus rotundus, Lolium rigidum, Portulaca oleracea, Salsola kali, Solanum nigrum) and crops (maize, tomato), which was subjected to different training, validation and test scenarios. Model inputs were adjusted in order to align them with the information represented by the UAV images. Initially, models were developed in balanced scenarios, gradually increasing label numbers to assess their performance. Inception-ResNet-v2 achieved over 90% accuracy with 400 labels, while ResNet152 and VGG16 required 600 and 800 labels, respectively, for similar accuracy. In a more complex and realistic scenarios with unbalanced datasets, Inception-ResNet-v2 outperformed, likely due to its deeper architecture and enhanced capability to capture intricate features and patterns within UAV images. The study emphasized the importance of the minority-to-majority species ratio in unbalanced datasets, which affects minority species classification. To prevent misclassification, it is crucial to determine the right number of labels for CNN model training and validation. Weed maps were generated after species classification using the Faster R–CNN algorithm as an object detector. This advancement in methodology facilitates the precise and efficient implementation of SSWM techniques.

Study on the Co-Development Path between the Ideological and Political Thinking of Physical Education Curriculum and the Consciousness of the Chinese Nation Community in the Frontier Minority Areas

Cast firmly the Chinese nation community consciousness, is to safeguard the fundamental interests of the ethnic groups is the inevitable requirement of realizing the great rejuvenation of the Chinese nation is the inevitable requirement of consolidating and developing equality unity mutual assistance harmonious socialist ethnic relations is the inevitable requirement of the party's ethnic work to open up new prospects. Yunnan is located in the southwest border of the motherland, is one of the most ethnic minority species and multi-ethnic cultural resources in the region. Yunnan border universities must integrate ideological and political education teaching resources, guide students to cast firmly the Chinese nation community consciousness, cultivate national feelings, enhance national confidence and pride, promote social common development. Based on this, this article will start from the perspective of ideological and political education in physical education courses, explore the mechanism of ideological and political education in physical education courses to cast firmly the Chinese nation community consciousness, discuss the strengthening of education on the national college students in Yunnan to cast firmly the national community consciousness, guide the youth of all ethnic groups to forge ahead, maintain national unity, build a beautiful home, which has practical significance for the high-quality, leapfrog development of Yunnan, and explore its practical path.

CO‐induzierte Dimer‐Dissoziation verursacht Gem‐Dicarbonyl‐Bildung auf einem Einzelatom‐Katalysator‐Modell

AbstractDie Fähigkeit, mehrere Reaktanten an derselben aktiven Stelle zu koordinieren ist eine wichtige Voraussetzung für die breite Anwendbarkeit der Einzelatom‐Katalyse. Modellkatalysatoren sind ideal, um den Zusammenhang zwischen der Geometrie der aktiven Stelle und der Bindung der Reaktanten zu untersuchen, da die Struktur der Einkristalloberflächen genau bestimmt werden kann. Die Adsorbate können mit Hilfe der Rastertunnelmikroskopie (STM) abgebildet werden; dadurch sind direkte Vergleiche mit der Dichtefunktionaltheorie möglich. In dieser Studie verfolgen wir mit Hilfe von STM‐Bildsequenzen einzelne Rh1‐Adatome und Rh2‐Dimere auf Fe3O4(001), während CO bei Raumtemperatur dosiert wird. Die CO‐Adsorption auf Rh1‐Adatomen führt ausschließlich zu stabilen Rh1CO‐Monocarbonylen, bei denen das Rh‐Atom die bevorzugte pseudo‐quadratisch planare Koordination erzielt. In geringem Maß bilden sich auch Rh1(CO)2 Gem‐Dicarbonyl‐Adsorbate; diese entstehen jedoch ausschließlich durch das Aufbrechen von Rh2 Dimeren; der Reaktionsweg führt über ein instabiles Rh2(CO)3 Zwischenprodukt. Unsere Ergebnisse veranschaulichen, wie Minderheitenspezies, die für (über die Probenfläche mittelnde) Spektroskopie‐Methoden unsichtbar sind, eine wichtige Rolle in katalytischen Systemen spielen können, und zeigen, dass die Zersetzung von Dimeren oder kleinen Clustern ein Weg sein kann, um reaktive, metastabile Konfigurationen in der Einzelatom‐Katalyse zu erzeugen.

CO-Induced Dimer Decay Responsible for Gem-Dicarbonyl Formation on a Model Single-Atom Catalyst.

The ability to coordinate multiple reactants at the same active site is important for the wide-spread applicability of single-atom catalysis. Model catalysts are ideal to investigate the link between active site geometry and reactant binding, because the structure of single-crystal surfaces can be precisely determined, the adsorbates imaged by scanning tunneling microscopy (STM), and direct comparisons made to density functional theory. In this study, we follow the evolution of Rh1 adatoms and minority Rh2 dimers on Fe3O4(001) during exposure to CO using time-lapse STM at room temperature. CO adsorption at Rh1 sites results exclusively in stable Rh1CO monocarbonyls, because the Rh atom adapts its coordination to create a stable pseudo-square planar environment. Rh1(CO)2 gem-dicarbonyl species are also observed, but these form exclusively through the breakup of Rh2 dimers via an unstable Rh2(CO)3 intermediate. Overall, our results illustrate how minority species invisible to area-averaging spectra can play an important role in catalytic systems, and show that the decomposition of dimers or small clusters can be an avenue to produce reactive, metastable configurations in single-atom catalysis.

The status of minority species and young individuals of the terrestrial malacofauna in Capsian and Neolithic populations in eastern Maghreb

The status of minority species and young individuals of the terrestrial malacofauna in Capsian and Neolithic populations in eastern Maghreb

Foodborne and waterborne Arcobacter species exhibit a high virulent activity in Caco-2

Infection mechanisms of Arcobacter remain uncertain. This study aimed to determine whether 65 food and waterborne isolates of at least six species were able to adhere and invade Caco-2 cells; and whether this ability could be related to cadF, cj1349, ciaB, and/or hecA, specific genetic markers related to host cell adhesion and invasion. All adhered and invaded the cells, and harboured at least two virulence markers. The mean virulent activity shown by A. butzleri was superior to that of A. cryaerophilus (p < 0.05); but the mean adhesion and invasion values of A. lanthieri, A. skirrowii, and A. vitoriensis were even higher. Sewage isolates were significantly (p < 0.05) more adherent and invasive than the rest, and their associated gene content was higher (p < 0.05). For the first time, an association between cadF and hecA and a high adhesion capability was identified (p < 0.05). The results provide new data on the pathogenic potential of Arcobacter species present in food and water by highlighting the superiority of A. butzleri over A. cryarophilus; providing evidence on the virulence of minority species as A. lanthieri and A. vitoriensis; and confirming sewage as an important source of potentially more virulent arcobacters.

Occurrence, Activity and Control Options Against Biting Midges (Diptera: Culicoides) in Horses

Abstract Biting midges are insects which annoy horses as they cause discomfort and by the sucking of blood, they cause painful lesions that, in certain cases, can trigger acute allergic reactions. They also act as potential vectors of many pathogens of bacterial, viral and parasitic origin. The aim of this study was to investigate seasonal dynamics, abundance and species composition of biting midges, and implementing protection options at the Equestrian centre of the University of Veterinary Medicine and Pharmacy (UVMP) in Košice in the years 2021 and 2022. During this time period (of 2021 and 2022), we captured 4797 biting midges. Our results showed that in 2021 the most frequently captured species were C. obsoletus/C. scoticus (prevalence 86.6 %), followed by C. punctatus and C. pulicaris (prevalence 5.37 % and 3.86 %, resp.). In addition, C. lupicaris, C. newsteadi, C. furcillatus, C. festivipennis, C. slovacus, C. tauricus, C. clastrieri, C. dewulfi, C. fagineus and C. circumscriptus were identified as the minority species. In this year, the highest abundance of these insects (1758 biting midges) was observed at the end of June. In 2022, we detected a clear dominance of C. obsoletus/C. scoticus (prevalence 97.0 %) and the highest number of biting midges (655) was captured in mid-May). In this year, the minority species included, C. pulicaris, C. punctatus and C. lupicaris. The identification of the host blood showed that man (Homo sapiens) was the dominant host, namely of 80 % of the examined biting midges of species C. obsoletus/C. scoticus, C. dewulfi, C. punctatus and C. festivipennis. In one female of species C. fagineus we identified the host blood from horses (Equus caballusi). In 2022, we detected the blood of a domestic rabbit (Oryctolagus cuniculus) in the species of C. obsoletus/C. scoticus.

Rejection methods for vegetation mapping using hyperspectral airborne data

ABSTRACT Vegetation mapping from remote sensing data has proven useful for monitoring ecosystems at local, regional and global scales. Generally based on supervised classification methods, ecosystem mapping needs representative and consistent labelling. Such completeness is often difficult to achieve and requires the exclusion of minority species poorly represented in the studied scene in the training base. This exclusion leads to wrong predictions in the resulting map. In this study, the use of a posteriori classification rejection methods to limit the errors associated with minority species was evaluated in three different mapping scenarios: classification according to vegetation layers, prediction of genera from various vegetation types from low vegetation to trees and mapping of habitat (assemblages of species). For this purpose, several supervised classification methods based on Support Vector Machines (SVM), Random Forests (RF) and Regularized Logistic Regression (RLR) algorithms were first applied to hyperspectral images covering the reflective domain. On these classifications, the usual evaluation methods (confusion matrix and its derivatives calculated on an independent test set composed of the majority species) showed performances similar to those of the state-of-the-art. However, the introduction of a new score taking into account minority species demonstrated the need to include them in the evaluation process to provide robust performance quantification representing map effectiveness. Three a posteriori rejection methods, based on simple thresholding, K-means and SVM algorithms, were well suited to monitor minority species. The performance gain depended on the mapping scenario, the machine learning model and the rejection method. An increase in performance with the inclusion of minority species of up to 12% could be observed through the new score. These methods also detected a similar proportion of prediction errors associated with predominant species

A mixed-species shoal including fewer heterospecifics is preferred by jack mackerel Trachurus japonicus juveniles

Mixed-species shoals of fishes were reported from various environments such as coral reefs and temperate lakes. The driving mechanism of forming mixed-species shoal can be either haphazard or a preferential choice by an individual. Here, we tested if jack mackerel Trachurus japonicus, a temperate marine pelagic fish, could choose a shoal composition using vision based on a choice experiment. Shoal preference of jack mackerel juveniles was evaluated by presenting shoals comprising one to four heterospecifics (half-lined cardinal Ostorhinchus semilineatus) out of four shoal members to the focal fish. When both conspecific and heterospecific shoals were presented to a single jack mackerel, the focal fish showed a preference for the conspecific rather than heterospecific shoal, indicating that they can choose a conspecific shoal based on the visual information. However, when a focal fish encountered both conspecific and mixed-species shoals including fewer heterospecifics (one out of four individuals), the latter was preferred. The result implies that jack mackerel can judge a preferable composition of shoal using visual information. The inclusion of fewer heterospecifics may be exploiting oddity effects, whereby minority species are exposed to relatively high vulnerability to predators, as well as resulting in reduced competition for food while maintaining predator vigilance in a shoal.

Mapping the structural trends in zinc aluminosilicate glasses.

The structure of zinc aluminosilicate glasses with the composition (ZnO)x(Al2O3)y(SiO2)1-x-y, where 0 ≤ x < 1, 0 ≤ y < 1, and x + y < 1, was investigated over a wide composition range by combining neutron and high-energy x-ray diffraction with 27Al magic angle spinning nuclear magnetic resonance spectroscopy. The results were interpreted using an analytical model for the composition-dependent structure in which the zinc ions do not act as network formers. Four-coordinated aluminum atoms were found to be in the majority for all the investigated glasses, with five-coordinated aluminum atoms as the main minority species. Mean Al-O bond distances of 1.764(5) and 1.855(5) Å were obtained for the four- and five-coordinated aluminum atoms, respectively. The coordination environment of zinc was not observed to be invariant. Instead, it is dependent on whether zinc plays a predominantly network-modifying or charge-compensating role and, therefore, varies systematically with the glass composition. The Zn-O coordination number and bond distance were found to be 4.36(9) and 2.00(1) Å, respectively, for the network-modifying role vs 5.96(10) and 2.08(1) Å, respectively, for the charge-compensating role. The more open coordination environment of the charge-compensator is related to an enhanced probability of zinc finding bridging oxygen atoms as nearest-neighbors, reflecting a change in the connectivity of the glass network comprising four-coordinated silicon and aluminum atoms as the alumina content is increased.

Experimental and Kinetic Study on Laminar Burning Velocities of High Ratio Hydrogen Addition to CH4+O2+N2 and NG+O2+N2 Flames

In 2020, energy-related CO2 emissions reached 31.5 Gt, leading to an unprecedented atmospheric CO2 level of 412.5 ppm. Hydrogen blending in natural gas (NG) is a solution for maximizing clean energy utilization and enabling long-distance H2 transport through pipelines. However, insufficient comprehension concerning the combustion characteristics of NG, specifically when blended with a high proportion of hydrogen up to 80%, particularly with minority species, persists. Utilizing the heat flux method at room temperature and 1 atm, this experiment investigated the laminar burning velocities of CH4/NG/H2/air/He flames incorporating minority species, specifically C2H6 and C3H8, within NG. The results point out the regularity of SL enhancement, reaching its maximum at an equivalence ratio of 1.4. Furthermore, the propensity for the enhancement of laminar burning velocity aligned with the observed thermoacoustic oscillation instability during fuel-rich regimes. The experimental findings were contrasted with kinetic simulations, utilizing the GRI 3.0 and San Diego mechanisms to facilitate analysis. The inclusion of H2 augments the chemical reactions within the preheating zone, while the thermal effect from temperature is negligible. Both experimental and simulated results revealed that CH4 and NG with a large proportion of H2 had no difference, no matter whether from a laminar burning velocity or a kinetic analysis aspect.

X-ray Absorption Spectroscopy Reveals Mechanisms of Calcium and Silicon Fouling on Reverse Osmosis Membranes Used in Wastewater Reclamation

Reverse osmosis (RO) is widely employed to provide clean water from nontraditional sources (e.g., seawater or municipal wastewater). One of its key challenges is membrane fouling, which leads to reduced flux and increased operational costs. Despite its practical relevance, fundamental understanding of membrane fouling is limited. Toward this end, we investigated calcium (Ca) and silicon (Si) fouling under real RO feed conditions using μ-X-ray fluorescence (μ-XRF) mapping and μ-X-ray absorption near-edge fine structure (μ-XANES) spectroscopy. These techniques are distinctly suited to identify the spatial distribution and (local) chemical speciation of foulants, thereby providing unique insight into the mechanisms of fouling under realistic conditions. Specifically, we investigated RO membranes harvested from a pilot-scale RO system operated at the Orange County Water District (OCWD) Groundwater Replenishment System (GWRS) Advanced Water Purification (AWP) Facility, which received the same feed water as the full-scale plant. Both Ca and Si were found to be abundant in the fouling layer. Despite the use of a commercial antiscalant to inhibit mineral formation, several Ca minerals were present in the fouling layer as minority species, including sulfates, phosphates, and carbonates; most of these minerals were found in particles that were aligned with the feed spacer used to separate the membranes. In contrast, organic-bound Ca and silica occurred across the entire membrane. Our work provides novel insight into the synergistic mechanism of RO fouling by Ca, Si, and organics on RO membranes.

Effect of Fluorinated Carboxylic Acid Ester on Lithium Solvation as an Additive in Electrolyte and Low-Temperature Insight on Battery Performance

The fluorinated carboxylic acid esters are effective additives to improve the performance of lithium-ion batteries (LIBs). Among them, 2,2,2-trifluoroethylbutyrate (TFEB) has been reported as a good additive to enhance battery performance, especially at low temperatures. It becomes a consensus that the solvation structure around lithium ion plays a crucial role in LIBs. However, it remains a mystery how such additives impact lithium solvation and how the impact changes at low temperatures. In this work, classical molecular dynamics (MD) simulations were conducted to investigate microcosmic mechanisms of the influence of TFEB on a typical commercial electrolyte composed of lithium hexafluorophosphate (LiPF6)/ethylene carbonate (EC)/ethyl methyl carbonate (EMC) in LIBs. Although TFEB is a minority species, it can significantly modify the lithium solvation structure. The introduction of TFEB facilitates the participation of anion in the solvation shell, due to its weaker coordination ability compared to EC/EMC, which was elucidated by the detailed analyses including radial distribution functions, cluster analysis, cage residence time, etc. We further investigated a series of TFEB analogs (TFEA, ETFA, and MPFP) and found that a moderately weak coordination ability is essential in the design of electrolytes. Furthermore, it was uncovered not only that the coordination number of the anions will decrease at low temperatures but also that their orientations are significantly changed. We demonstrated that the introduction of TFEB will alleviate this tendency, which may be advantageous to low-temperature performance. In summary, the critical role of fluorinated additives is uncovered by our MD simulations in modulating the Li+ solvation structure and improving the low-temperature performance of LIB, which provides references to the design strategy of novel low-temperature fluorine-containing additive-based electrolytes.

Hydrodynamic effects in kinetics of phase separation in binary fluids: Critical versus off-critical compositions.

Via hydrodynamics-preserving molecular dynamics simulations we study growth phenomena in a phase-separating symmetric binary mixture model. We quench high-temperature homogeneous configurations to state points inside the miscibility gap, for various mixture compositions. For compositions at the symmetric or critical value we capture the rapid linear viscous hydrodynamic growth due to advective transport of material through tubelike interconnected domains. For state points very close to any of the branches of the coexistence curve, the growth in the system, following nucleation of disconnected droplets of the minority species, occurs via a coalescence mechanism. Using state-of-the-art techniques, we have identified that these droplets, between collisions, exhibit diffusive motion. The value of the exponent for the power-law growth, related to this diffusive coalescence mechanism, has been estimated. While the exponent nicely agrees with that for the growth via the well-known Lifshitz-Slyozov particle diffusion mechanism, the amplitude is stronger. For the intermediate compositions we observe initial rapid growth that matches the expectations for viscous or inertial hydrodynamic pictures. However, at later times these types of growth cross over to the exponent that is decided by the diffusive coalescence mechanism.

Experimental evaluation of waterlogging and drought tolerance of essential Prunus species in central Europe

Fruit-bearing and flowering minority tree species, such as many species from the Prunus genus, are essential for multiple ecosystem services in the landscape. Although common, but never dominating, these minority species are often overlooked compared to commercial timber trees in relation to climate change. Induced stress on trees through climate change in central Europe will not only be caused by drought but also by extreme precipitation and pluvial flooding. This study experimentally address this by testing both waterlogging and drought tolerance in three key species of Prunus for central Europe that naturally span a wide variation of habitat conditions. The selected species Prunus mahaleb, Prunus avium and Prunus padus were subjected to both drought and waterlogging in a greenhouse experiment. Plant functionality in the form of midday leaf water potential, stomatal conductance and turgor loss point together with different aspects of biomass allocation and growth was tested. All included species lost their stomatal conductance and leaf water potential within a few days in the waterlogging treatment. Only P. padus had the capacity to recover with new leaves after the waterlogging ended, suggesting that avoidance strategies though leaf shedding can be a complementary mechanism to withstand waterlogging. P. padus kept its stomatal conductance and water potential for the longest time in the drought treatment followed by P. mahaleb and P.avium. This longevity in the drought treatment for P. padus could be explained by both tolerance strategies through lower turgor loss point, but also avoidance strategies with fast changes in growth and higher allocation of biomass to the roots. There is a clear risk that ecosystem service from Prunus species in the landscape can be negatively affected not only by drought but also by increased events of waterlogging. This highlights the need for including minority species and also other climate stressors in addition to drought in the planning and management of multifunctional landscapes.