Climate drives loss of phylogenetic diversity in a grassland community

© 2019 National Academy of Sciences. All rights reserved. While climate change has already profoundly influenced biodiversity through local extinctions, range shifts, and altered interactions, its effects on the evolutionary history contained within sets of coexisting species—or phylogenetic community diversity—have yet to be documented. Phylogenetic community diversity may be a proxy for the diversity of functional strategies that can help sustain ecological systems in the face of disturbances. Under climatic warming, phylogenetic diversity may be especially vulnerable to decline in plant communities in warm, water-limited regions, as intensified water stress eliminates drought-intolerant species that may be relicts of past wetter climates and may be distantly related to coexisting species. Here, we document a 19-y decline of phylogenetic diversity in a grassland community as moisture became less abundant and predictable at a critical time of the year. This decline was strongest in native forbs, particularly those with high specific leaf area, a trait indicating drought sensitivity. This decline occurred at the small spatial scale where species interact, but the larger regional community has so far been buffered against loss of phylogenetic diversity by its high levels of physical and biotic heterogeneity

Epiphyte type and sampling height impact mesofauna communities in Douglas-fir trees

Branches and boles of trees in wet forests are often carpeted with lichens and bryophytes capable of providing periodically saturated habitat suitable for microfauna, animals that include tardigrades, rotifers, nematodes, mites, and springtails. Although resident microfauna likely exhibit habitat preferences structured by fine-scale environmental factors, previous studies rarely report associations between microfaunal communities and habitat type (e.g., communities that develop in lichens vs. bryophytes). Microfaunal communities were examined across three types of epiphyte and three sampling heights to capture gradients of microenvironment. Tardigrades, rotifers, and nematodes were significantly more abundant in bryophytes than fruticose lichen or foliose lichen. Eight tardigrade species and four tardigrade taxa were found, representing two classes, three orders, six families, and eight genera. Tardigrade community composition was significantly different between bryophytes, foliose lichen, fruticose lichen, and sampling heights. We show that microenvironmental factors including epiphyte type and sampling height shape microfaunal communities and may mirror the environmental preferences of their epiphyte hosts

Data from: Functional traits and community composition: a comparison among community-weighted means, weighted correlations, and multilevel models

1. Of the several approaches that are used to analyze functional trait-environment relationships, the most popular is community-weighted mean regressions (CWMr) in which species trait values are averaged at the site level and then regressed against environmental variables. Other approaches include model-based methods and weighted correlations of different metrics of trait-environment associations, the best known of which is the fourth-corner correlation method. 2. We investigated these three general statistical approaches for trait-environment associations: CWMr, five weighted correlation metrics (Peres-Neto et al. 2017), and two multilevel models (MLM) using four different methods for computing p-values. We first compared the methods applied to a plant community dataset. To determine the validity of the statistical conclusions, we then performed a simulation study. 3. CWMr gave highly significant associations for both traits, while the other methods gave a mix of support. CWMr had inflated type I errors for some simulation scenarios, implying that the significant results for the data could be spurious. The weighted correlation methods had generally good type I error control but had low power. One of the multilevel models, that from Jamil et al. (2013), had both good type I error control and high power when an appropriate method was used to obtain p-values. In particular, if there was no correlation among species in their abundances among sites, a parametric bootstrap likelihood ratio test (LRT) gave the best power. When there was correlation among species in their abundances, a conditional parametric LRT had correct type I errors but had lower power. 4. There is no overall best method for identifying trait-environment associations. For the simple task of testing, one-by-one, associations between single environmental variables and single traits, the weighted correlations with permutation tests all had good type I error control, and their ease of implementation is an advantage. For the more complex task of multivariate analyses and model fitting, and when high statistical power is needed, we recommend MLM2 (Jamil et al. 2013); however, care must be taken to ensure against inflated type I errors. Because CWMr exhibited highly inflated type I error rates, it should always be avoided. 2. We investigated these three general statistical approaches for trait-environment associations: CWMr, five weighted correlation metrics (Peres-Neto et al. 2017), and two multilevel models (MLM) using five different methods for computing p-values. We first compared the methods applied to a plant community dataset. To determine the validity of the statistical conclusions, we then performed a simulation study. 3. CWMr gave highly significant associations for both traits, while the other methods gave a mix of support. CWMr had inflated type I errors for some simulation scenarios. The weighted correlation methods had generally good type I error control but had low power. One of the multilevel models, that from Jamil et al. (2013), had both good type I error control and high power when an appropriate method was used to obtain p-values. In particular, if there was no correlation among species in their abundances among sites, a parametric bootstrap likelihood ratio test (LRT) gave the best power. When there was correlation among species in their abundances, a conditional parametric LRT had correct type I errors but suffered from low power. 4. There is no overall best method for identifying trait-environment associations. For the simple task of testing, one-by-one, associations between single environmental variables and single traits, the weighted correlations with permutation tests all had good type I error control, and their ease of implementation is an advantage. For the more complex task of multivariate analyses and model fitting, and when high statistical power is needed, we recommend MLM2 (Jamil et al. 2013); however, care must be taken to ensure against inflated type I errors. Because CWMr exhibited highly inflated type I error rates, it should be avoided

Data from: Early- and late-flowering guilds respond differently to landscape spatial structure

1. Species with unique phenologies have distinct trait syndromes and environmental affinities, yet there has been little exploration of whether community assembly processes differ for plants with different phenologies. In this study, we ask whether early- and late-blooming species differ in the ways that dispersal, persistence, and resource-acquisition traits shape plant occurrence patterns in patchy habitats. 2. We sampled plant communities in 51 Ozark dolomite glade grasslands, which range in size from 100 ha. We modelled the occurrence of 71 spring- and 43 summer-blooming grassland species these patches, using as predictors both environmental variables (landscape structure, soil resources) and plant traits related to dispersal, longevity, and resource acquisition. We were especially interested in how the environmental variables and plant traits interacted to determine the occurrence of phenological strategies in habitats that vary in size and isolation. 3. Summer-blooming species with better persistence and dispersal abilities had higher relative frequencies in smaller, more isolated habitat patches, and summer-blooming species with higher specific leaf area—suggesting fast growth and low stress tolerance—were more likely to occur in patches with greater soil organic matter and clay content. However, spring-blooming species showed much weaker interactions between functional traits and environmental gradients, perhaps because environmental conditions are less harsh in spring than in summer. 4. Synthesis: Several axes of plant life history variation may simultaneously influence community responses to habitat connectivity. In this case, explicitly considering plant phenology helped identify generalizable relationships between functional traits and landscape spatial structure

Observation of WWWWWW Production in pppp Collisions at s\sqrt s =13 TeV with the ATLAS Detector

International audienceThis Letter reports the observation of $WWW$ production and a measurement of its cross section using 139 fb$^{-1}$ of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. Events with two same-sign leptons (electrons or muons) and at least two jets, as well as events with three charged leptons, are selected. A multivariate technique is then used to discriminate between signal and background events. Events from $WWW$ production are observed with a significance of 8.0 standard deviations, where the expectation is 5.4 standard deviations. The inclusive $WWW$ production cross section is measured to be $820 \pm 100\,\text{(stat)} \pm 80\,\text{(syst)}$ fb, approximately 2.6 standard deviations from the predicted cross section of $511 \pm 18$ fb calculated at next-to-leading-order QCD and leading-order electroweak accuracy

Observation of WWWWWW Production in pppp Collisions at s\sqrt s =13 TeV with the ATLAS Detector

International audienceThis Letter reports the observation of $WWW$ production and a measurement of its cross section using 139 fb$^{-1}$ of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. Events with two same-sign leptons (electrons or muons) and at least two jets, as well as events with three charged leptons, are selected. A multivariate technique is then used to discriminate between signal and background events. Events from $WWW$ production are observed with a significance of 8.0 standard deviations, where the expectation is 5.4 standard deviations. The inclusive $WWW$ production cross section is measured to be $820 \pm 100\,\text{(stat)} \pm 80\,\text{(syst)}$ fb, approximately 2.6 standard deviations from the predicted cross section of $511 \pm 18$ fb calculated at next-to-leading-order QCD and leading-order electroweak accuracy

Observation of WWWWWW Production in pppp Collisions at s\sqrt s =13 TeV with the ATLAS Detector

International audienceThis Letter reports the observation of $WWW$ production and a measurement of its cross section using 139 fb$^{-1}$ of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. Events with two same-sign leptons (electrons or muons) and at least two jets, as well as events with three charged leptons, are selected. A multivariate technique is then used to discriminate between signal and background events. Events from $WWW$ production are observed with a significance of 8.0 standard deviations, where the expectation is 5.4 standard deviations. The inclusive $WWW$ production cross section is measured to be $820 \pm 100\,\text{(stat)} \pm 80\,\text{(syst)}$ fb, approximately 2.6 standard deviations from the predicted cross section of $511 \pm 18$ fb calculated at next-to-leading-order QCD and leading-order electroweak accuracy

Observation of WWWWWW Production in pppp Collisions at s\sqrt s =13 TeV with the ATLAS Detector

International audienceThis Letter reports the observation of $WWW$ production and a measurement of its cross section using 139 fb$^{-1}$ of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. Events with two same-sign leptons (electrons or muons) and at least two jets, as well as events with three charged leptons, are selected. A multivariate technique is then used to discriminate between signal and background events. Events from $WWW$ production are observed with a significance of 8.0 standard deviations, where the expectation is 5.4 standard deviations. The inclusive $WWW$ production cross section is measured to be $820 \pm 100\,\text{(stat)} \pm 80\,\text{(syst)}$ fb, approximately 2.6 standard deviations from the predicted cross section of $511 \pm 18$ fb calculated at next-to-leading-order QCD and leading-order electroweak accuracy