Computing the Skewness of the Phylogenetic Mean Pairwise Distance in Linear Time

The phylogenetic Mean Pairwise Distance (MPD) is one of the most popular measures for computing the phylogenetic distance between a given group of species. More specifically, for a phylogenetic tree T and for a set of species R represented by a subset of the leaf nodes of T, the MPD of R is equal to the average cost of all possible simple paths in T that connect pairs of nodes in R. Among other phylogenetic measures, the MPD is used as a tool for deciding if the species of a given group R are closely related. To do this, it is important to compute not only the value of the MPD for this group but also the expectation, the variance, and the skewness of this metric. Although efficient algorithms have been developed for computing the expectation and the variance the MPD, there has been no approach so far for computing the skewness of this measure. In the present work we describe how to compute the skewness of the MPD on a tree T optimally, in Theta(n) time; here n is the size of the tree T. So far this is the first result that leads to an exact, let alone efficient, computation of the skewness for any popular phylogenetic distance measure. Moreover, we show how we can compute in Theta(n) time several interesting quantities in T that can be possibly used as building blocks for computing efficiently the skewness of other phylogenetic measures.Comment: Peer-reviewed and presented as part of the 13th Workshop on Algorithms in Bioinformatics (WABI2013

Disequilibrium in Trait-Climate Relationships of Trees and Birds

Climate change is expected to drive changes in the structure of ecological assemblages, but these responses might show considerable time lags. If these lags are large, then the observed composition of assemblages will fall out of equilibrium with current climatic conditions. This disequilibrium has several expected signatures, including trends in the magnitude of climate relationships through time and stronger climate relationships across space than through time. Here, I describe spatial and temporal patterns of functional assemblage composition of birds and trees and ask whether there is evidence of disequilibrium between climate and functional assemblage structure. I used bird assemblage data from the Breeding Bird Survey (BBS) and tree data from the Forest Inventory and Analysis program (FIA), in both cases spanning the continental United States and covering the time period 1970–2016. To describe functional assemblage composition, I used the community weighted means of five functional traits for trees and six traits for birds, and fit linear models to explain the variation in composition through time and across space. For most traits, spatial relationships were much stronger than temporal relationships, consistent with lagged responses of assemblages to climate change. Several of the traits showed trends over the study period, in some cases associated with trends in mean annual temperature. Others showed dynamics in the spatial relationships between climate and trait values. For example, the mean clutch size of birds depended only weakly on temperature in the early study period, but the relationship became strongly negative by 2016. While precipitation was often an important predictor of spatial patterns of functional composition, it was typically weakly correlated with the temporal patterns. This likely reflects the fact that temperature experienced more consistent long-term trends over the study period, whereas large year-to-year fluctuations in precipitation prevent composition from ever coming into equilibrium with precipitation in a particular year. Overall, there was substantial evidence of disequilibrium between functional assemblage composition and climate

Establishing macroecological trait datasets: digitalization, extrapolation, and validation of diet preferences in terrestrial mammals worldwide

Ecological trait data are essential for understanding the broad-scale distribution of biodiversity and its response to global change. For animals, diet represents a fundamental aspect of species’ evolutionary adaptations, ecological and functional roles, and trophic interactions. However, the importance of diet for macroevolutionary and macroecological dynamics remains little explored, partly because of the lack of comprehensive trait datasets. We compiled and evaluated a comprehensive global dataset of diet preferences of mammals (“MammalDIET”). Diet information was digitized from two global and cladewide data sources and errors of data entry by multiple data recorders were assessed. We then developed a hierarchical extrapolation procedure to fill-in diet information for species with missing information. Missing data were extrapolated with information from other taxonomic levels (genus, other species within the same genus, or family) and this extrapolation was subsequently validated both internally (with a jack-knife approach applied to the compiled species-level diet data) and externally (using independent species-level diet information from a comprehensive continentwide data source). Finally, we grouped mammal species into trophic levels and dietary guilds, and their species richness as well as their proportion of total richness were mapped at a global scale for those diet categories with good validation results. The success rate of correctly digitizing data was 94%, indicating that the consistency in data entry among multiple recorders was high. Data sources provided species-level diet information for a total of 2033 species (38% of all 5364 terrestrial mammal species, based on the IUCN taxonomy). For the remaining 3331 species, diet information was mostly extrapolated from genus-level diet information (48% of all terrestrial mammal species), and only rarely from other species within the same genus (6%) or from family level (8%). Internal and external validation showed that: (1) extrapolations were most reliable for primary food items; (2) several diet categories (“Animal”, “Mammal”, “Invertebrate”, “Plant”, “Seed”, “Fruit”, and “Leaf”) had high proportions of correctly predicted diet ranks; and (3) the potential of correctly extrapolating specific diet categories varied both within and among clades. Global maps of species richness and proportion showed congruence among trophic levels, but also substantial discrepancies between dietary guilds. MammalDIET provides a comprehensive, unique and freely available dataset on diet preferences for all terrestrial mammals worldwide. It enables broad-scale analyses for specific trophic levels and dietary guilds, and a first assessment of trait conservatism in mammalian diet preferences at a global scale. The digitalization, extrapolation and validation procedures could be transferable to other trait data and taxa

Mammal predator and prey species richness are strongly linked at macroscales

Predator-prey interactions play an important role for species composition and community dynamics at local scales, but their importance in shaping large-scale gradients of species richness remains unexplored. Here, we use global range maps, structural equation models (SEM), and comprehensive databases of dietary preferences and body masses of all terrestrial, non-volant mammals worldwide, to test whether (1) prey bottom-up or predator top-down relationships are important drivers of broad-scale species richness gradients once the environment and human influence have been accounted for, (2) predator-prey richness associations vary among biogeographic regions, and (3) body size influences large-scale covariation between predators and prey. SEMs including only productivity, climate, and human factors explained a high proportion of variance in prey richness (R2 = 0.56) but considerably less in predator richness (R2 = 0.13). Adding predator-to-prey or prey-topredator paths strongly increased the explained variance in both cases (prey R2 = 0.79, predator R2 = 0.57), suggesting that predator-prey interactions play an important role in driving global diversity gradients. Prey bottom-up effects prevailed over productivity, climate, and human influence to explain predator richness, whereas productivity and climate were more important than predator top-down effects for explaining prey richness, although predator top-down effects were still significant. Global predator-prey associations were not reproduced in all regions, indicating that distinct paleoclimate and evolutionary histories (Africa and Australia) may alter species interactions across trophic levels. Stronger crosstrophic- level associations were recorded within categories of similar body size (e.g., large prey to large predators) than between them (e.g., large prey to small predators), suggesting that mass-related energetic and physiological constraints influence broad-scale richness links, especially for large-bodied mammals. Overall, our results support the idea that trophic interactions can be important drivers of large-scale species richness gradients in combination with environmental effects. © 2013 by the Ecological Society of America

The Inflationary Gravity Waves in light of recent Cosmic Microwave Background Anisotropies data

One of the major predictions of inflation is the existence of a stochastic background of cosmological gravitational waves (GW). These gravitational waves can induce significant temperature anisotropies in the Cosmic Microwave Background (CMB) on the angular scales recently probed by the Archeops experiment. Here, we perform a combined analysis of Archeops together with information from other CMB experiments and/or cosmological datasets, in order to constrain the amplitude of the GW background. We find that, for a scale-invariant GW background, the ratio of tensor/scalar perturbations at the CMB quadrupole is now constrained to be $r \leq 0.43$ at 95% c.l., while the bound on the spectral index of primordial density fluctuations is $n_S=0.97_{-0.12}^{+0.10}$. We discuss the implications for future GW detections through CMB polarization measurements.Comment: 5 pages, 3 figures. Replaced with final updated proof versio

The macroecology of animal versus wind pollination: ecological factors are more important than historical climate stability

Background: The relative frequency of wind and animal pollinated plants is non-randomly distributed across the globe and numerous hypotheses have been raised for the greater occurrence of wind pollination in some habitats and towards higher latitudes. To date, however, there has been no comprehensive global investigation of these hypotheses. Aims: Investigating a range of hypotheses for the role of biotic and abiotic factors as determinants of the global variation in animal versus wind pollination. Methods: We analysed 67 plant communities ranging from 70º North to 34º South. For these we determined habitat type, species richness, insularity, topographic heterogeneity, current climate and Late-Quaternary climate change. The predictive effects of these factors on the proportion of wind- and animal-pollinated plants were tested using correlations, ordinary least squares (OLS) and logistic regression analyses with information-theoretic model selection. Results: The proportion of animal-pollinated plant species was positively associated with plant species richness and current temperature. Furthermore, in forest, animal pollination was positively related to precipitation. Historical climate was only weakly and idiosyncratically correlated with animal pollination. Conclusion: Results were consistent with the hypothesised reduced chance for wind-transported pollen reaching conspecific flowers in species-rich communities, fewer constraints on nectar production in warm and wet habitats, and reduced relative effectiveness of wind dispersal in humid areas. There was little evidence of a legacy of historical climate change affecting these patterns

Current climate, isolation and history drive global patterns of tree phylogenetic endemism

AimWe mapped global patterns of tree phylogenetic endemism (PE) to identify hotspots and test hypotheses about possible drivers. Specifically, we tested hypotheses related to current climate, geographical characteristics and historical conditions and assessed their relative importance in shaping PE patterns.LocationGlobal.Time periodWe used the present distribution of trees, and predictors covering conditions from the mid‐Miocene to present.Major taxa studiedAll seed‐bearing trees.MethodsWe compiled distributions for 58,542 tree species across 463 regions worldwide, matched these to a recent phylogeny of seed plants and calculated PE for each region. We used a suite of predictor variables describing current climate (e.g., mean annual temperature), geographical characteristics (e.g., isolation) and historical conditions (e.g., tree cover at the Last Glacial Maximum) in a spatial regression model to explain variation in PE.ResultsTree PE was highest on islands, and was higher closer to the equator. All three groups of predictor variables contributed substantially to the PE pattern. Isolation and topographic heterogeneity promoted high PE, as did high current tree cover. Among mainland regions, temperature seasonality was strongly negatively related to PE, while mean annual temperature was positively related to PE on islands. Some relationships differed among the major floristic regions. For example, tree cover at the Last Glacial Maximum was a positive predictor of PE in the Palaeotropics, while tree cover at the Miocene was a negative predictor of PE in the Neotropics.Main conclusionsGlobally, PE can be explained by a combination of geographical, historical and current factors. Some geographical variables appear to be key predictors of PE. However, the impact of historic and current climate variables differs considerably among the major floristic regions, reflecting their unique histories. Hence, the current distribution of trees is the result of globally relevant geographical drivers and regional climatic histories.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153237/1/geb13001.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153237/2/geb13001_am.pd

Community and Ecosystem-level Changes in a Species-rich Tallgrass Prairie Restoration

Changes in the plant community and ecosystem properties that follow the conversion of agriculture to restored tallgrass prairies are poorly understood. Beginning in 1995, we established a species-rich, restored prairie chronosequence where -3 ha of agricultural land have been converted to tallgrass prairie each year. Our goals were to examine differences in ecosystem properties between these restored prairies and adjacent agricultural fields and to determine changes in, and potential interactions between, the plant community and ecosystem properties that occur over time in the restored prairies. During the summers of 2000-2002, we examined species cover, soil C and N, potential net C and N mineralization, litter mass, soil texture, and bulk density across the 6- to 8-year-old prairie chronosequence and adjacent agricultural fields in southern Minnesota. We also established experimentally fertilized, watered, and control plots in the prairie chronosequence to examine the degree of nitrogen limitation on aboveground and belowground net primary production (ANPP and BNPP). Large shifts in functional diversity occurred within three growing seasons. First-year prairies were dominated by annuals and biennials. By the second growing season, perennial native composites had become dominant, followed by a significant shift to warm-season C4 grasses in prairies ?3 yr old. Ecosystem properties that changed with the rise of C4 grasses included increased BNPP, litter mass, and C mineralization rates and decreased N mineralization rates. ANPP increased significantly with N fertilization but did not vary between young and old prairies with dramatically different plant community composition. Total soil C and N were not significantly different between prairie and agricultural soils in the depths examined (0-10, 10-20, 20-35, 35-50, 50-65 cm). We compared the results from our species-rich prairie restoration to published data on ecosystem function in other restored grasslands, such as Conservation Reserve Program (CRP) and old-field successional sites. Results suggest that rapid changes in functional diversity can have large impacts on ecosystem-level properties, causing community- and system-level dynamics in species-rich prairie restorations to converge with those from low-diversity managed grasslands

Science for a wilder Anthropocene: synthesis and future directions for trophic rewilding research

Trophic rewilding is an ecological restoration strategy that uses species introductions to restore top-down trophic interactions and associated trophic cascades to promote self-regulating biodiverse ecosystems. Given the importance of large animals in trophic cascades and their widespread losses and resulting trophic downgrading, it often focuses on restoring functional megafaunas. Trophic rewilding is increasingly being implemented for conservation, but remains controversial. Here, we provide a synthesis of its current scientific basis, highlighting trophic cascades as the key conceptual framework, discussing the main lessons learned from ongoing rewilding projects, systematically reviewing the current literature, and highlighting unintentional rewilding and spontaneous wildlife comebacks as underused sources of information. Together, these lines of evidence show that trophic cascades may be restored via species reintroductions and ecological replacements. It is clear, however, that megafauna effects may be affected by poorly understood trophic complexity effects and interactions with landscape settings, human activities, and other factors. Unfortunately, empirical research on trophic rewilding is still rare, fragmented, and geographically biased, with the literature dominated by essays and opinion pieces. We highlight the need for applied programs to include hypothesis testing and science-based monitoring, and outline priorities for future research, notably assessing the role of trophic complexity, interplay with landscape settings, land use, and climate change, as well as developing the global scope for rewilding and tools to optimize benefits and reduce human–wildlife conflicts. Finally, we recommend developing a decision framework for species selection, building on functional and phylogenetic information and with attention to the potential contribution from synthetic biology