Find research datasets worth reusing

opencc-by-4.0May 2020View details →

Experimental data of the paper "Trial-based Heuristic Tree Search for MDPs with Factored Action Spaces"

This data set contains the code of our planner and of the planner that was used as baseline, the benchmark set that was used to perform experiments as well as the parsed values and basic reports that are reported in the paper. More information can be found in the README that is also included.

opencc-by-4.0Nov 2020View details →

Supplementary Material: "A Density-Based Algorithm for the Detection of Individual Trees from LiDAR Data"

Supplementary Material This material regards the paper entitled "A Density-Based Algorithm for the Detection of Individual Trees from LiDAR Data". The Readme.txt file explains all the contents of the data package, which consists of the data supporting the paper and the MATLAB script for the Individual Tree Detection and Measurement (ITDM). Please cite the related article if using the data or the script. Latella, M., Sola, F., & Camporeale, C. (2021). A Density-Based Algorithm for the Detection of Individual Trees from LiDAR Data. Remote Sensing, 13(2), 322.

opencc-by-sa-4.0Jan 2019View details →

Projection of potential future tree cover persistence for 2029 based on the global model

Tree cover persistence projection results for 2029 based on the global model under a business-as-usual scenario.

opencc-by-sa-4.0Jan 2019View details →

Projection of potential future tree cover persistence for 2029 based on the six regional models

Tree cover persistence projection results for 2029 based on the six regional models under a business-as-usual scenario.

opencc-by-4.0Nov 2022View details →

Reconstitution of August SPEI3 drought index based on the δ18O in tree-ring cellulose for the Eastern Carpathian, for the period 1331-2012CE

Here we report the reconstruction of the summer (June to August) Standardized Precipitation-Evapotranspiration Index (SPEI3), for the period 1331-2012CE, for eastern Europe, based on annually-resolved stable oxygen isotope ratios (δ18O) from Pinus cembra L. tree-ring cellulose from the Călimani Mountains, Romania. Variations of the δ18O values capture the August SPEI3 changes both at high and low frequencies (from interannual to multidecadal scales). The palaeoclimate potential of stable isotopes in Pinus cembra L. (Swiss stone pine) tree-ring cellulose from the Călimani Mountains has been demonstrated by Nagavciuc et al. 2019 (DOI: 10.1002/joc.6349), showing that δ18O variability allows high-resolution paleoclimatic reconstructions over the eastern part of Europe, where few such reconstructions are available.

opencc-by-4.0Jun 2020View details →

Neighbor-joining phylogenetic tree based on 16S rRNA sequences.

Supplementary Figure (S1): Bayesian 50% majority rule phylogram of 16S ribosomal RNA region showing the phylogenetic relationships among the bacterial isolates in our study. The newly generated sequences are preceded by red circle. The GenBank sequences are preceded by blue squares. The GenBank accession number appears after the species name. Numbers above the branches represent Bayesian posterior probabilities (≥ 0.90), and the maximum parsimony bootstrap support values are given below the branches (≥70%). The out group used for tree construction preceded by empty circle.

opencc-by-4.0Sep 2015View details →

Figure 1. Bayesian phylogenetic tree inferred from the 640 in Two new Geoplaninae species (Platyhelminthes: Continenticola) from Southern Brazil based on an integrative taxonomic approach

Figure 1. Bayesian phylogenetic tree inferred from the 640-bp of cytochrome c oxidase subunit I gene under GTR + I + G model of sequence evolution. The two new species are highlighted in light grey (Cratera ochra sp. nov.) and dark grey (Obama maculipunctata sp. nov.). Values indicate support for each node according to the maximum posterior probabilities>70% and bootstrap support values> 70%, respectively.

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.

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Efficient genomics based 'end-to-end' selective tree breeding framework

Since their initiation in the 1950s, worldwide selective tree breeding programs followed the recurrent selection scheme of repeated cycles of selection, breeding (mating), and testing phases and essentially remained unchanged to accelerate this process or address environmental contingences and concerns. Here, we introduce an "end-to-end" selective tree breeding framework that: 1) leverages strategically preselected GWAS-based sequence data capturing trait architecture information, 2) generates unprecedented resolution of genealogical relationships among tested individuals, and 3) leads to the elimination of the breeding phase through the utilization of readily available wind-pollinated (OP) families. Individuals' breeding values generated from multi-trait multi-site analysis were also used in an optimum contribution selection protocol to effectively manage genetic gain/co-ancestry trade-offs and traits' correlated response to selection. The proof-of-concept study involved a 40-year-old spruce OP testing population growing on three sites in British Columbia, Canada, clearly demonstrating our method's superiority in capturing most of the available genetic gains in a substantially reduced timeline relative to the traditional approach. The proposed framework is expected to increase the efficiency of existing selective breeding programs, accelerate the start of new programs for ecologically and environmentally important tree species, and address climate-change caused biotic and abiotic stress concerns more effectively.

opencc-zeroDec 2022View details →

Figure 2 in Cicada minimum age tree: Cryptic speciation and exponentially increasing base substitution rates in recent geologic time

Figure 2. Cicada timetree built by BEAST v1.X, applying 1,534 bp COI sequence. OUTs with isolate number: our own analyzed specimens shown in Table 1, and others: from GenBank/DDJB. In outgroup Hemiptera; #: analyzed family by Johnson et al. (2018); % analyzed family by Misof et al. (2014). Inserted figure: Base substitution rate (= rate median shown at each node; substitutions per site per million year; s/s/myr) vs age (= posterior age shown at each node) diagram. Red approximate curve with its formula was drawn by Excel function, with the intersection for the curve = 0.0128 s/s/myr, the rate median shown on Tracer.

Figure 4 in Cicada minimum age tree: Cryptic speciation and exponentially increasing base substitution rates in recent geologic time

Figure 4. Number of base changes of transition and tansversion vs corrected pairwide distance diagram for whole mitochondrial gene.

Figure 1 in Cicada minimum age tree: Cryptic speciation and exponentially increasing base substitution rates in recent geologic time

Figure 1. Simplified cicada timetree built by BEAST v1.X, applying a 1,534 bp in maximum COI sequence. Inserted figure: Base substitution rate (= ratemedian shown at each node; substitutions per siteper millionyear; s/s/ myr) vsage (= posterior age shown at each node) diagram. Red approximate curve with its formula was drawn by an Excel function, with the intersection for the curve = 0.0128 s/s/myr, the rate median shown on Tracer.

Figure 3 in Cicada minimum age tree: Cryptic speciation and exponentially increasing base substitution rates in recent geologic time

Figure 3. Cicada timetree built by BEAST v1.X, applying 1,534 bp COI and 874 bp 18S rRNA sequences. OUTswith isolate number: our own analyzed specimens shown in Table 1, and others: from GenBank/DDJB. In outgroup Hemiptera; #: analyzed family by Johnson et al. (2018); % analyzed family by Misof et al. (2014). Inserted figure: Base substitution rate (= rate median shown at each node; substitutions per site per million year; s/s/myr) vs age (= posterior age shown at each node) diagram. Red approximatecurve with its formulawas drawn by Excel function, with the intersection for the curve = 0.0114 s/s/myr, the rate median shown on Tracer. Note that this rate is a little slower than thatsolely of COI in Figures 1 and 2, reflecting slowerrate of 18S rRNAthan COI (see Osozawa et al. 2017a).

opencc-by-4.0Dec 2021View details →

Text-fig. 9. Phylogenetic tree indicating the number of required character state changes (steps) under parsimony for various positions of Miranthus gen. nov. in a molecular based backbone tree (see material and methods for additional details). in Early Flowers Of Primuloid Ericales From The Late Cretaceous Of Portugal And Their Ecological And Phytogeographic Implications

Text-fig. 9. Phylogenetic tree indicating the number of required character state changes (steps) under parsimony for various positions of Miranthus gen. nov. in a molecular based backbone tree (see material and methods for additional details).

opencc-by-4.0Sep 2023View details →

Priority landscapes for tree-based restoration in Rwanda

These priority maps highlight landscapes where the promotion of tree-based restoration practices is expected to yield higher benefits compared to possible interventions in non-priority landscapes. It is important to note that the priority maps created should not be considered as final, but as part of the process in identifying intervention areas for tree planting in Rwanda. Key further steps in prioritization include stakeholder consultations to incorporate their perspecives and field observations to further define the most adequate interventions. For more information on the methodology please consult the following documents:  Pedercini, F., Dawson, I.K., Kindt, R., Tadesse, W., Moestrup, S., Abiyu, A., Lillesø, J.P.B., Van Schoubroeck, F., McMullin, S., Carsan, S. and Mausch, K., 2021. Priority landscapes for tree-based restoration in Ethiopia. In ICRAF Working Paper. World Agroforestry Centre. [https://dx.doi.org/10.5716/WP21037.PDF; https://patspo.shinyapps.io/Restoration_Ethiopia/] Pedercini, F., Kindt, R., Dawson, I., Lillesø, JPB., Mukuralinda, A., Ndayambaje, J. D., Jamnadass, R., Graudal, L. (2023). Priority landscapes for tree-based restoration in Rwanda: a spatially explicit approach to prioritize areas for intervention. TREPA report. Pedercini, F., Kindt, R., Graudal, L. (2024). Priority landscapes for tree-based restoration in Rwanda: a spatially explicit approach to prioritize areas for intervention. World Bank report.

opencc-by-4.0Aug 2021View details →

FI GU R E 3 Maximum likelihood phylogenetic tree of the Hyalospheniformes with a focus on Apodera, Alocodera, and Padaungiella based on COI gene sequences. Bootstrap values (bs) and Bayesian posterior probabilities (p.p.) are indicated respectively between branches. COI sequences from genera other than Apodera were retrieved from GenBank in Superficially described and ignored for 92 years, rediscovered and emended: Apodera angatakere (Amoebozoa: Arcellinida: Hyalospheniformes) is a new flagship testate amoeba taxon from Aotearoa (New Zealand)

FI GU R E 3 Maximum likelihood phylogenetic tree of the Hyalospheniformes with a focus on Apodera, Alocodera, and Padaungiella based on COI gene sequences. Bootstrap values (bs) and Bayesian posterior probabilities (p.p.) are indicated respectively between branches. COI sequences from genera other than Apodera were retrieved from GenBank

opencc-by-4.0Dec 2021View details →

Text-fig. 13. Macrophotographs of the fossil stems from Mhengere. a: large (90 cm diameter) palm tree trunk in situ; b: external view of the outer roots at the base of the trunk; average diameter of single root is 7 mm; c, d: cross-sections of a fragment of trunk showing the random distribution of equal-sized fibre vascular bundles throughout the trunk, the so-called Coccos-type. in Stratigraphy, Chronology And Palaeontology Of The Tertiary Rocks Of The Cheringoma Plateau, Mozambique

Text-fig. 13. Macrophotographs of the fossil stems from Mhengere. a: large (90 cm diameter) palm tree trunk in situ; b: external view of the outer roots at the base of the trunk; average diameter of single root is 7 mm; c, d: cross-sections of a fragment of trunk showing the random distribution of equal-sized fibre vascular bundles throughout the trunk, the so-called Coccos-type.