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FIG. 2 in Terminalia carinata Sabatier & J.Engel, sp. nov. (Combretaceae), a new large tree species from the Guiana shield revealed by re-examination of material previously identified as T. guyanensis Eichler

FIG. 2. — Terminalia carinata Sabatier & J.Engel, sp. nov.: A, B, inflorescences; C, fruiting branch (note fruit keeled on one side and flat on the other); D, stem with leaves; note: i) the typical Terminalia arrangement of leaves clustered at twig tips; and ii) the leaf margin revolute at very base; E, trunk; F, trunk slash; A, B, Mori & Gracie 18653; C, Sabatier et al. 4891 (type specimen); D, Sabatier 2309. A, B, Photographs by Carol Gracie; C, D, photographs by Daniel Sabatier; E, F, photographs by Julien Engel.

FIG. 1 in Terminalia carinata Sabatier & J.Engel, sp. nov. (Combretaceae), a new large tree species from the Guiana shield revealed by re-examination of material previously identified as T. guyanensis Eichler

FIG. 1. — Terminalia carinata Sabatier & J.Engel, sp. nov.: A, stem with leaves; B, detail of abaxial leaf surface; C, inflorescences with a young shoot of leaves; D, flower; E, longitudinal section of flower; F, three views of stamens; G, fruits; H, transverse section of fruit; A, B, Boom & Mori 2134 (CAY); C-F, Mori & Gracie 18653 (CAY); G, H, Mori & Boom 15121 (CAY). Drawn by Laurence Ramon. Scale bars: A, C, G, H, 1 cm; B, D, E, 1 mm; F, 0.5 mm.

FIG. 4 in Terminalia carinata Sabatier & J.Engel, sp. nov. (Combretaceae), a new large tree species from the Guiana shield revealed by re-examination of material previously identified as T. guyanensis Eichler

FIG. 4. — Distribution of Terminalia guyanensis Eichler and Terminalia carinata Sabatier & J.Engel, sp. nov.: (·) T. guyanensis and (▲) T. carinata Sabatier & J.Engel, sp. nov., herbarium specimens; () T. guyanensis and () T. carinata Sabatier & J.Engel, sp. nov., observations (no voucher) from the GUYADIV and GUYAFOR networks (Engel 2015).

FIG. 6 in Terminalia carinata Sabatier & J.Engel, sp. nov. (Combretaceae), a new large tree species from the Guiana shield revealed by re-examination of material previously identified as T. guyanensis Eichler

FIG. 6. — Terminalia guyanensis Eichler: A, fruiting branch; B, inflorescences; C, trunk; D, bark with a machete slash; A, Sabatier & Molino 5682 (CAY); B-D, Sabatier et al. 6018 (P). A-D, Photographs by Daniel Sabatier.

opencc-zeroDec 2018View details →

Wildfires and climate change push low-elevation forests across a critical climate threshold for tree regeneration

Climate change is increasing fire activity in the western United States, which has the potential to accelerate climate-induced shifts in vegetation communities. Wildfire can catalyze vegetation change by killing adult trees that could otherwise persist in climate conditions no longer suitable for seedling establishment and survival. Recently documented declines in postfire conifer recruitment in the western United States may be an example of this phenomenon. However, the role of annual climate variation and its interaction with long-term climate trends in driving these changes is poorly resolved. Here we examine the relationship between annual climate and postfire tree regeneration of two dominant, low-elevation conifers (ponderosa pine and Douglas-fir) using annually resolved establishment dates from 2,935 destructively sampled trees from 33 wildfires across four regions in the western United States. We show that regeneration had a nonlinear response to annual climate conditions, with distinct thresholds for recruitment based on vapor pressure deficit, soil moisture, and maximum surface temperature. At dry sites across our study region, seasonal to annual climate conditions over the past 20 years have crossed these thresholds, such that conditions have become increasingly unsuitable for regeneration. High fire severity and low seed availability further reduced the probability of postfire regeneration. Together, our results demonstrate that climate change combined with high severity fire is leading to increasingly fewer opportunities for seedlings to establish after wildfires and may lead to ecosystem transitions in low-elevation ponderosa pine and Douglas-fir forests across the western United States.

opencc-by-4.0Dec 2010View details →

Figs. 17–20 in Description of a new species of Anthocoris (Hemiptera: Heteroptera: Anthocoridae) from southern India, associated with striped mealybug on purple orchid tree

Figs. 17–20. Anthocoris muraleedharani Yamada, sp. nov. 17 – adult habitus; 18 – mature nymph feeding on solenopsis mealybug; 19 – young nymph feeding on solenopsis mealybug; 20 – eggs inserted into plant tissue (arrows show exposed operculum of egg).

opencc-by-4.0Dec 2010View details →

Figs. 1–6 in Description of a new species of Anthocoris (Hemiptera: Heteroptera: Anthocoridae) from southern India, associated with striped mealybug on purple orchid tree

Figs. 1–6. Anthocoris muraleedharani Yamada, sp. nov., paratypes, male (1–2, 5–6) and female (3–4). 1 – head and pronotum, dorsal view; 2–3 – antennae; 4 – left fore wing, dorsal view; 5 – ostiolar peritreme and evaporatorium, left lateroventral view; 6 – abdominal sterna II–III, ventral view. Scale bars = 0.5 mm for 1–4, 6; 0.1 mm for 5.

opencc-by-4.0Dec 2010View details →

Figs. 12–16 in Description of a new species of Anthocoris (Hemiptera: Heteroptera: Anthocoridae) from southern India, associated with striped mealybug on purple orchid tree

Figs. 12–16. Anthocoris muraleedharani Yamada, sp. nov. 12–13 – habitus of holotype, dorsal and lateral views; 14–15 – head and pronotum, male (14) and female (15), dorsal view; 16 – ostiolar peritreme and evaporatorium, female, left lateroventral view. Scale bars = 1.0 mm for 12–13; 0.5 mm for 14–15: 0.1 mm for 16.

opencc-by-4.0Jan 2019View details →

Figure 3 in Changes in a soil microarthropod community in the vicinity of dominant tree species under trampling management at the Safari Zoological Center, Israel

Figure 3 The taxon richness, Shannon index, Simpson index, and Evenness index (mean ± SD) of soil Acari at different treatment sites at the Safari Zoological Center, Israel, December 2013. OE = open places under enclosure, OT = open places under trampling; EE = E. camaldulensis canopy habitat under enclosure, ET =E. camaldulensis canopy habitat under trampling, TE =T. aphylla canopy habitat under enclosure, TT =T. aphylla canopy habitat under trampling, CE =C. sempervirens canopy habitat under enclosure, CT =C. sempervirens canopy habitat under trampling. Different letters represent significance at p<0.05.

opencc-by-4.0Jan 2019View details →

Figure 2 in Changes in a soil microarthropod community in the vicinity of dominant tree species under trampling management at the Safari Zoological Center, Israel

Figure 2 The abundance (individuals per 10 g dry soil substrate; mean ± SD) of soil microarthropod taxa extracted from core samples at different treatment sites at the Safari Zoological Center, Israel, December 2013. OE = open places under enclosure, OT = open places under trampling; EE =E. camaldulensis canopy habitat under enclosure, ET =E. camaldulensis canopy habitat under trampling, TE = T. aphylla canopy habitat under enclosure, TT =T. aphylla canopy habitat under trampling, CE = C. sempervirens canopy habitat under enclosure, CT =C. sempervirens canopy habitat under trampling. Different letters within the same group represent significance at p<0.05.

opencc-by-4.0Jan 2019View details →

Figure 1 in Changes in a soil microarthropod community in the vicinity of dominant tree species under trampling management at the Safari Zoological Center, Israel

Figure 1 Location of study sites at the Safari Zoological Center, Israel. OE = open places under enclosure, OT = open places under trampling; EE =E. camaldulensis canopy habitat under enclosure, ET = E. camaldulensis canopy habitat under trampling, TE =T. aphylla canopy habitat under enclosure, TT = T. aphylla canopy habitat under trampling, CE =C. sempervirens canopy habitat under enclosure, CT = C. sempervirens canopy habitat under trampling.

opencc-by-4.0Dec 2016View details →

Fig. 7. Maximum-likelihood tree for the mitochondrial DNA gene Cytochrome Oxidase C subunit 1 in A new species of the catfish Neoplecostomus (Loricariidae: Neoplecostominae) from a coastal drainage in southeastern Brazil

Fig. 7. Maximum-likelihood tree for the mitochondrial DNA gene Cytochrome Oxidase C subunit 1 for specimens of Neoplecostomus microps from rio Paraíba do Sul, rio Guapi- Açu and rio Macaé, and of Neoplecostomus paraty, using TN93+G model (n=21). Neoplecostomus paranensis and Neoplecostomus ribeirensis were used as outgroups.

opencc-zeroDec 2015View details →

Data from: Urban trees reduce nutrient leaching to groundwater

Many urban waterways suffer from excess nitrogen (N) and phosphorus (P) feeding algal blooms, which cause lower water clarity and oxygen levels, bad odor and taste, and the loss of desirable species. Nutrient movement from land to water is likely to be influenced by urban vegetation, but there are few empirical studies addressing this. In this study, we examined whether or not urban trees can reduce nutrient leaching to groundwater, an important nutrient export pathway that has received less attention than stormwater. We characterized leaching beneath thirty-three trees of fourteen species, and seven open turfgrass areas, across three city parks in Saint Paul, Minnesota. We installed lysimeters at 60 cm depth to collect soil water approximately biweekly from July 2011 through October 2013, except during winter and drought periods, measured dissolved organic carbon (C), N, and P in soil water, and modeled water fluxes using the BROOK90 hydrologic model. We also measured soil nutrient pools (bulk C and N, KCl-extractable inorganic N, Brays-P), tree tissue nutrient concentrations (C, N, and P of green leaves, leaf litter, and roots), and canopy size parameters (leaf biomass, leaf area index) to explore correlations with nutrient leaching. Trees had similar or lower N leaching than turfgrass in 2012 but higher N leaching in 2013; trees reduced P leaching compared with turfgrass in both 2012 and 2013, with lower leaching under deciduous than evergreen trees. Scaling up our measurements to an urban subwatershed of the Mississippi River (~17,400 ha, containing roughly 1.5 million trees), we estimated that trees reduced P leaching to groundwater by 533 kg in 2012 (0.031 kg/ha or 3.1 kg/km2) and 1201 kg in 2013 (0.069 kg/ha or 6.9 kg/km2). Removing these same amounts of P using stormwater infrastructure would cost $2.2 million and $5.0 million per year (2012 and 2013 removal amounts, respectively).

opencc-zeroDec 2018View details →

Data from: Soil organic carbon stability in forests: distinct effects of tree species identity and traits

Rising atmospheric CO2 concentrations have increased interest in the potential for forest ecosystems and soils to act as carbon (C) sinks. While soil organic C contents often vary with tree species identity, little is known about if, and how, tree species influence the stability of C in soil. Using a 40‐year‐old common garden experiment with replicated plots of eleven temperate tree species, we investigated relationships between soil organic matter (SOM) stability in mineral soils and 17 ecological factors (including tree tissue chemistry, magnitude of organic matter inputs and their turnover, microbial community descriptors, and soil physico‐chemical properties). We measured five SOM stability indices, including heterotrophic respiration, C in aggregate‐occluded particulate organic matter (POM) and mineral‐associated SOM, and bulk SOM δ15N and ∆14C. The stability of SOM varied substantially among tree species and this variability was independent of the amount of organic C in soils. Thus, when considering forest soils as C sinks, the stability of C stocks must be considered in addition to their size. Further, our results suggest tree species regulate soil C stability via the composition of their tissues, especially roots. Stability of SOM appeared to be greater (as indicated by higher δ15N and reduced respiration) beneath species with higher concentrations of nitrogen and lower amounts of acid‐insoluble compounds in their roots, while SOM stability appeared to be lower (as indicated by higher respiration and lower proportions of C in aggregate‐occluded POM) beneath species with higher tissue calcium contents. The proportion of C in mineral‐associated SOM and bulk soil ∆14C, though, were negligibly dependent on tree species traits, likely reflecting an insensitivity of some SOM pools to decadal‐scale shifts in ecological factors. Strategies aiming to increase soil C stocks may thus focus on particulate C pools, which can more easily be manipulated and are most sensitive to climate change.

opencc-zeroDec 2019View details →

Data from: An analysis of mating biases in trees

Assortative mating is a deviation from random mating based on phenotypic similarity. As it is much better studied in animals than in plants, we investigate for trees whether kinship of realized mating pairs deviates from what is expected from the set of potential mates and use this information to infer mating biases that may result from kin recognition and/or assortative mating. Our analysis covers twenty species of trees for which microsatellite data is available for adult populations (potential mates) as well as seed arrays. We test whether mean relatedness of observed mating pairs deviates from null expectations that only take pollen dispersal distances into account (estimated from the same dataset). This allows to identify elevated as well as reduced kinship among realized mating pairs, indicative of positive and negative assortative mating, respectively. The test is also able to distinguish elevated biparental inbreeding that occurs solely as a result of related pairs growing closer to each other from further assortativeness. Assortative mating in trees appears potentially common but not ubiquitous: nine data sets show mating bias with elevated inbreeding, nine do not deviate significantly from the null expectation, and two show mating bias with reduced inbreeding. While our datasets lack direct information on phenology, our investigation of the phenological literature for each species identifies flowering phenology as a potential driver of positive assortative mating (leading to elevated inbreeding) in trees. Since active kin recognition provides an alternative hypothesis for these patterns, we encourage further investigations on the processes and traits that influence mating patterns in trees.

opencc-by-4.0Jun 2021View details →

Fig. 27. Maximum likelihood tree from the concatenated data set with COI, 28S and 18S in Revision of the Merodon bombiformis group (Diptera: Syrphidae) - rare and endemic African hoverflies

Fig. 27. Maximum likelihood tree from the concatenated data set with COI, 28S and 18S rRNA gene sequences.

opencc-zeroDec 2016View details →

Data from: Enriching the ant tree of life: enhanced UCE bait set for genome-scale phylogenetics of ants and other Hymenoptera

1. Targeted enrichment of conserved genomic regions (e.g., ultraconserved elements or UCEs) has emerged as a promising tool for inferring evolutionary history in many organismal groups. Because the UCE approach is still relatively new, much remains to be learned about how best to identify UCE loci and design baits to enrich them. 2. We test an updated UCE identification and bait design workflow for the insect order Hymenoptera, with a particular focus on ants. The new strategy augments a previous bait design for Hymenoptera by (a) changing the parameters by which conserved genomic regions are identified and retained, and (b) increasing the number of genomes used for locus identification and bait design. We perform in vitro validation of the approach in ants by synthesizing an ant-specific bait set that targets UCE loci and a set of "legacy" phylogenetic markers. Using this bait set, we generate new data for 84 taxa (16/17 ant subfamilies) and extract loci from an additional 17 genome-enabled taxa. We then use these data to examine UCE capture success and phylogenetic performance across ants. We also test the workability of extracting legacy markers from enriched samples and combining the data with published data sets. 3. The updated bait design (hym-v2) contained a total of 2,590-targeted UCE loci for Hymenoptera, significantly increasing the number of loci relative to the original bait set (hym-v1; 1,510 loci). Across 38 genome-enabled Hymenoptera and 84 enriched samples, experiments demonstrated a high and unbiased capture success rate, with the mean locus enrichment rate being 2,214 loci per sample. Phylogenomic analyses of ants produced a robust tree that included strong support for previously uncertain relationships. Complementing the UCE results, we successfully enriched legacy markers, combined the data with published Sanger data sets, and generated a comprehensive ant phylogeny containing 1,060 terminals. 4. Overall, the new UCE bait design strategy resulted in an enhanced bait set for genome-scale phylogenetics in ants and likely all of Hymenoptera. Our in vitro tests demonstrate the utility of the updated design workflow, providing evidence that this approach could be applied to any organismal group with available genomic information.

opencc-by-4.0Mar 2016View details →

Demonstrative simulations of L-PEACH: a computer-based model to understand how peach trees grow

L-PEACH is a computer-based model that simulates source-sink interactions, architecture and physiology of peach trees (Allen et al., 2005, 2006, 2007). The model integrates important concepts related to water transport and carbon assimilation, distribution, and use within the tree (DeJong et al., 2011). L-PEACH is able to simulate crop yield responses to commercial practices such as fruit thinning (Lopez et al., 2008) and pruning (Smith et al., 2008) and could be useful for making fruit growers understand how to optimize these operations. In this work we present several demonstrative simulations of L-PEACH to complement the existing references about L-PEACH and demonstrate its value to study, understand and teach how trees grow (DeJong et al., 2008). The FIRST SIMULATION corresponds with the version of L-PEACH that runs on a daily time-step (L-PEACH-d) (Lopez et al., 2008, 2010). The simulation shows the growth of a peach tree over three years. The color of the stem indicates the direction of the movement of carbon within the tree (white indicates no flux of carbon, increasing apical flux of carbon from light yellow to red, and increasing basal flux of carbon from light blue to deep purple) (see details of colors in Allen et al., 2005). During this simulation the tree was stopped during the dormant season between years and the trees were pruned by the model operator in a manner that is similar to how trees would be pruned when growing in an orchard.  Also during the first year of tree growth, grafting is simulated by cutting the tree back in early spring and allowing the tree to grow again as it would in a tree nursery.  After this first year the tree is cut back to a single trunk in the same manner as is commonly done when a tree is transplanted from a tree nursery to a commercial fruit orchard. In the SECOND SIMULATION a detailed section of the tree was selected to better appreciate the realism of leaf and fruit growth and in the THIRD SIMULATION we show how to prune a peach tree to a V-system. Responses to pruning were modelled based on the concept of apical dominance as described in Smith et al. (2008) and Lopez et al. (2008). Subsequent simulations correspond to the last version of the L-PEACH model that includes a xylem circuit so that the diurnal water potential of each organ could be simulated along with its physiological functioning and growth. Sub-models for leaf transpiration, soil water potential and the soil-plant interface were also incorporated to provide the driving force and pathway for water flow. In the FOURTH SIMULATION we presented the effect of different irrigation treatments (control irrigation and drought irrigation) on tree development, growth and fruit yield (Da Silva et al., 2011; 2014). L-PEACH-h was also use to illustrate the effect of severity of pruning in tree growth (FIFTH SIMULATION). We tested three levels of pruning: soft, control, and hard. The simulation indicates how trees that received hard pruning are able to recover a similar tree size than control and soft pruned trees due to the generation of vigorous shoots in response to hard pruning. The SIXTH SIMULATION was generated to demonstrate that L-PEACH can be also used to simulate the effect of size-controlling rootstock in tree growth (Da Silva et al., 2015). In this simulation we compared tree growth with a standard rootstock (Control) and a size-controlling rootstock (Rootstock) by reducing the hydraulic conductance of the ‘rootstock” piece (base of the trunk) by 50% in the size-controlling rootstock to simulate a reduction in vessel diameters and consequently reduced hydraulic conductance in that part of the tree. After four years of simulated growth, the virtual tree on the dwarfing rootstock was substantially smaller than the virtual tree on the control rootstock. What you can’t see in the movies is that the L-PEACH model calculates the distribution of light in the tree canopy as the tree grows and the rate of photosynthesis in each leaf during a simulated day or hour (depending on whether the daily or hourly models are used for the simulation). Then the distribution and use of photo-assimilates are calculated by the methods described in the papers cited below. The simulations are based on real environmental input data (light, temperature, day length, etc. collected from a real weather station located near a peach orchard) and development of tree architecture is based on developmental principles governing tree growth and detailed measurements of  shoots of peach trees (see references). Description of files Simulation 1: L-PEACH-d over three years of growth. Simulation 2: Detailed growth of leaves and fruit using L-PEACH. Simulation 3: Pruning L-PEACH-d to a v-system. Simulation 4: Control irrigation vs. Drought irrigation using L-PEACH-h. Simulation 5: Reactions to soft, control and hard pruning using L-PEACH-h. Simulation 6: Simulating the effect of size-controlling rootstock using L-PEACH-h.

opencc-by-4.0Jul 2016View details →

Robot Self-Assembly as Adaptive Growth Process: Collective Selection of Seed Position and Self-Organizing Tree-Structures

Autonomous self-assembly allows to create structures and scaffolds on demand and automatically. The desired structure may be predetermined or alternatively it is the result of an artificial growth process that adapts to environmental features and to the intermediate structure itself. In a self-organizing and decentralized control approach the robots interact only locally and form the structure collectively. Designing a complete approach that allows the robot group to collectively decide on where to start the self-assembly, that adapts at runtime to environmental conditions, and that guarantees the structural stability is challenging and does not yet exist. We present an approach to self-assembly inspired by diffusion-limited aggregation that generates an adaptive structure reacting to environmental conditions in an artificial growth process. During a preparatory stage the robots collectively decide where to start the self-assembly also depending on environmental conditions. In the actual self-assembly stage, the robots create tree-like structures that grow towards light. We report the results of robot self-assembly experiments with 50 Kilobots. Our results demonstrate how an adaptive growth process can be implemented in robots. We explain how our approach will be extended to a 3-d growth process and how robot self-assembly as an open-ended adaptive growth process opens up a multiplicity of future opportunities.