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The latest blooming peach at Byron is P.I. 101686, Ta Tao #24, from Shandong, China. In a preliminary trial as a rootstock, it delayed bloom in ‘Sunprince’ by 4-10 days and reduced trunk girth by one-third after 5 years, compared to ‘Flordaking’ and ‘Redglobe’ used as rootstocks It is not known if stock chilling requirement, stock vigor, virus interaction or unknown factors caused delayed bloom and reduced tree growth.
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This paper presents FAST-LIO2: a fast, robust, and versatile LiDAR-inertial odometry framework. Building on a highly efficient tightly-coupled iterated Kalman filter, FAST-LIO2 has two key novelties that allow fast, robust, and accurate LiDAR navigation (and mapping). The first one is directly registering raw points to the map (and subsequently update the map, i.e., mapping) without extracting features. This enables the exploitation of subtle features in the environment and hence increases the accuracy. The elimination of a hand-engineered feature extraction module also makes it naturally adaptable to emerging LiDARs of different scanning patterns; The second main novelty is maintaining a map by an incremental k-d tree data structure, ikd-Tree, that enables incremental updates (i.e., point insertion, delete) and dynamic re-balancing. Compared with existing dynamic data structures (octree, R*-tree, nanoflann k-d tree), ikd-Tree achieves superior overall performance while naturally supports downsampling on the tree. We conduct an exhaustive benchmark comparison in 19 sequences from a variety of open LiDAR datasets. FAST-LIO2 achieves consistently higher accuracy at a much lower computation load than other state-of-the-art LiDAR-inertial navigation systems. Various real-world experiments on solid-state LiDARs with small FoV are also conducted. Overall, FAST-LIO2 is computationally-efficient (e.g., up to 100 Hz odometry and mapping in large outdoor environments), robust (e.g., reliable pose estimation in cluttered indoor environments with rotation up to 1000 deg/s), versatile (i.e., applicable to both multi-line spinning and solid-state LiDARs, UAV and handheld platforms, and Intel and ARM-based processors), while still achieving higher accuracy than existing methods. Our implementation of the system FAST-LIO2, and the data structure ikd-Tree are both open-sourced on Github.
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This paper summarizes a broad range of studies that have examined influences of recent climate change on plant phenology or distribution. Spring events such as leafing and flowering have typically advanced, some by several weeks, with median advances of 4–5 d per degree Celsius. Autumn events, such as leaf coloring or leaf fall, have usually become delayed, though with more variability than spring events. Changes in summer events have been mixed. Phenological changes have varied geographically, as have recent temperature changes. Most studies of at least several decades duration show the initiation of rapid changes in the 1970s or 1980s, paralleling patterns of temperature change. Plants and animals in a given area have often responded at different rates to temperature change, which is likely to change patterns of interaction between plants and their pollinators and herbivores. Altitudinal changes in plant distributions have been demonstrated in several areas, especially in Scandinavia and in Mediterranean Europe, though these changes lag the measured temperature changes. Latitudinal changes in plant distribution have been demonstrated in only a few instances and it has been suggested that precipitation changes may have limited range shifts in response to warming in some areas. The observed and predicted changes in plant distribution and phenology have major implications for various ecological and evolutionary phenomena, including ecosystem productivity, species interactions, community structure, and conservation of biodiversity.
Summary Tree‐size distributions are changing in many natural forests around the world, and it is important to understand the underlying processes that are causing these changes. Here we use a classic conceptual framework – the shifting mosaic of patches model – to explore the ways in which competitive thinning and disturbance influence tree‐size distributions, and to consider the effects of temporal variability in disturbance frequency on the size structure of forests. We monitored 250 stands of Nothofagus solandri var. cliffortiodes (mountain beech), randomly distributed over 9000 hectares, for 19 years. Mountain beech is a light‐demanding species that forms monospecific forests in New Zealand mountains. For the purposes of our model, we assumed that each stand functions as an even‐aged population: it is initiated by a pulse of recruitment, undergoes competitive thinning as it matures, and is eventually destroyed by a disturbance event. The tree‐size distribution of the whole forest is driven partly by the frequency and temporal patchiness of disturbance events and partly by competitive processes within the constituent stands. Temporal changes in stem density and mean tree size were observed to be remarkably similar in all young stands, indicating that a consistent packing rule operates during this phase of stand development. A popular idea in the self‐thinning literature is that the maintenance of constant leaf area index (LAI) provides the mechanism for this packing rule, but our analyses suggest that LAI increased by about 30% during the thinning phase. We use leaf economic theory to develop a new packing rule based on light interception, and argue that LAI increases with stand age because of changes in canopy organisation. Smaller trees were significantly more likely to die than larger trees within the young stands. Tree‐diameter distributions within young stands were left skewed but those of older populations were normally distributed. These observations are consistent with asymmetric competition winnowing out small, suppressed trees from young stands but having less effect in older stands. Large‐scale disturbances created gaps of sufficient size to allow mass recruitment of seedlings in about 0.8% of stands each year. Older stands were most susceptible to such large‐scale disturbance, but the trend was weak. The diameter‐distribution of the whole Nothofagus forest was found to be approximately exponential in form. Simulation models only produced realistic diameter distributions when competitive packing rules and disturbance were included. Therefore, the shifting mosaic model provides a general framework for understand the ways in which these mortality processes determine forest size structure. The diameter distribution of the forest was not in equilibrium over the 19‐year study. Using simulation models, we show that temporal variability in disturbance frequency can generate enormous deviations in tree‐diameter distributions away from the long‐term mean, leading us to conclude that modern‐day disequilibrium in natural forests may be the legacy of past disturbance events.
1 The neutral theory debate has highlighted the scarcity of robust empirical estimates of the magnitude of competitive effects and responses within guilds of co-occurring tree species. Our analysis quantifies the relative magnitude of all possible pairwise competitive interactions within a guild of nine co-occurring tree species in temperate forests of northern, interior British Columbia, and explicitly partitions the competitive effects of neighbours into the effects of shading versus the residual effects of ‘crowding’, assumed to reflect below-ground competition. 2 Models that treated neighbours as equivalent in their competitive effects were the most parsimonious for the five species with the smallest sample sizes. For the remaining species (samples sizes of > 150 individuals), the best models estimated separate competition coefficients for all nine species of neighbours. We take this as evidence that species do indeed differ in their competitive effects, but that there can be a minimum sample size required to discriminate between them. 3 There was a strong size-dependency in potential growth. Six species showed an optimal growth at a size between 5 and 20 cm diameter. Potential growth declined moderately to strongly as diameter increased. Sensitivity to crowding varied as a function of tree size for five of the nine species; however, this response was not consistent by tree species. 4 The magnitude of reduction in growth due to crowding was greater on average than the reduction in growth due to shading, except for the two least shade tolerant conifers. Sensitivity to shading among the conifer species was correlated with their shade tolerance. 5 The per capita effects of crowding by different species of neighbours varied widely. A large number of the estimated pairwise per capita competition coefficients were very low. The relative magnitude of the strength of intra- versus interspecific competition also varied widely among the tree species. 6 Synthesis. Model selection techniques effectively separated above- and below-ground competition in complex forests, and allowed us to assess differences among species in competitive effects and responses. While below-ground effects were strong, they were due to proximity of neighbours from a very specific (and small) subset of strong competitors within the guild. Response to crowding varied with tree size but the nature of the relationship varied widely among the species.
Abstract. The long-term and large-scale dynamics of ecosystems are in large part determined by the performances of individual plants in competition with one another for light, water, and nutrients. Woody biomass, a pool of carbon (C) larger than 50% of atmospheric CO2, exists because of height-structured competition for light. However, most of the current Earth system models that predict climate change and C cycle feedbacks lack both a mechanistic formulation for height-structured competition for light and an explicit scaling from individual plants to the globe. In this study, we incorporate height-structured competition for light, competition for water, and explicit scaling from individuals to ecosystems into the land model version 3 (LM3) currently used in the Earth system models developed by the Geophysical Fluid Dynamics Laboratory (GFDL). The height-structured formulation is based on the perfect plasticity approximation (PPA), which has been shown to accurately scale from individual-level plant competition for light, water, and nutrients to the dynamics of whole communities. Because of the tractability of the PPA, the coupled LM3-PPA model is able to include a large number of phenomena across a range of spatial and temporal scales and still retain computational tractability, as well as close linkages to mathematically tractable forms of the model. We test a range of predictions against data from temperate broadleaved forests in the northern USA. The results show the model predictions agree with diurnal and annual C fluxes, growth rates of individual trees in the canopy and understory, tree size distributions, and species-level population dynamics during succession. We also show how the competitively optimal allocation strategy – the strategy that can competitively exclude all others – shifts as a function of the atmospheric CO2 concentration. This strategy is referred to as an evolutionarily stable strategy (ESS) in the ecological literature and is typically not the same as a productivity- or growth-maximizing strategy. Model simulations predict that C sinks caused by CO2 fertilization in forests limited by light and water will be down-regulated if allocation tracks changes in the competitive optimum. The implementation of the model in this paper is for temperate broadleaved forest trees, but the formulation of the model is general. It can be expanded to include other growth forms and physiologies simply by altering parameter values.
Drought intensity and frequency are increasing under global warming, with soil water availability now being a major factor limiting tree growth in circumboreal forests. Still, the adaptive capacity of trees in the face of future climatic regimes remains poorly documented. Using 1481 annually resolved tree-ring series from 29-yr-old trees, we evaluated the drought sensitivity of 43 white spruce (Picea glauca (Moench) Voss) populations established in a common garden experiment. We show that genetic variation among populations in response to drought plays a significant role in growth resilience. Local genetic adaptation allowed populations from drier geographical origins to grow better, as indicated by higher resilience to extreme drought events, compared with populations from more humid geographical origins. The substantial genetic variation found for growth resilience highlights the possibility of selecting for drought resilience in boreal conifers. As a major research outcome, we showed that adaptive genetic variation in response to changing local conditions can shape drought vulnerability at the intraspecific level. Our findings have wide implications for forest ecosystem management and conservation.
Phylogenetic comparative analysis is an approach to inferring evolutionary process from a combination of phylogenetic and phenotypic data. The last few years have seen increasingly sophisticated models employed in the evaluation of more and more detailed evolutionary hypotheses, including adaptive hypotheses with multiple selective optima and hypotheses with rate variation within and across lineages. The statistical performance of these sophisticated models has received relatively little systematic attention, however. We conducted an extensive simulation study to quantify the statistical properties of a class of models toward the simpler end of the spectrum that model phenotypic evolution using Ornstein-Uhlenbeck processes. We focused on identifying where, how, and why these methods break down so that users can apply them with greater understanding of their strengths and weaknesses. Our analysis identifies three key determinants of performance: a discriminability ratio, a signal-to-noise ratio, and the number of taxa sampled. Interestingly, we find that model-selection power can be high even in regions that were previously thought to be difficult, such as when tree size is small. On the other hand, we find that model parameters are in many circumstances difficult to estimate accurately, indicating a relative paucity of information in the data relative to these parameters. Nevertheless, we note that accurate model selection is often possible when parameters are only weakly identified. Our results have implications for more sophisticated methods inasmuch as the latter are generalizations of the case we study.
Summary 1. The study of invasiveness typically emphasizes early successional life‐history traits in exotic plants, which enable the capture of high resources in disturbed environments and rapid growth. A key issue in invasion dynamics is whether such behaviours come at the expense of traits such as low‐light survivorship, which allow species to become more dominant later in succession. 2. We used maximum‐likelihood analysis to compare the growth and survivorship of two exotic trees, Ailanthus altissima and Acer platanoides , with nine dominant native tree species in closed‐canopy forests in Connecticut, USA. Growth was modelled as a function of light and survivorship as a function of recent growth; combining models yielded estimates of light‐dependent mortality. 3. The exotic species had strikingly high growth rates, exceeding all native species at light levels ≥ 10% full sun, and growing 2.6 times faster than the fastest ‐growing native species at 80% full sun. At low‐light levels (< 3% full sun), however, growth rates of five native species exceeded both exotics. Exotic species survivorship (as a function of light‐driven growth) was strongly dependent on the degree of shading: at 1% full sun, the annual mortality rate of A. platanoides was 10% and A. altissima was 17%; only two native species had higher mortalities. However, at 5% full sun, A. platanoides ’ mortality was < 1%, superior to all but three native species. Mortality of all species dropped to < 1% by 10% full sun, except A. altissima whose mortality remained high at c . 10%. 4. A life‐history trade‐off analysis (based on radial growth, height allometry and low‐light survivorship) shows a nearly linear trade‐off for most species. The native species and Ailanthus follow the common life‐history trade‐off of low‐light survivorship vs. high‐light growth. However, A. platanoides diverges from this trade‐off pattern by combining very high growth rates with moderately high shade tolerance. 5. Simulations with SORTIE‐ND (a forest dynamics model) indicate that poor survivorship of A. altissima will limit it to disturbed sites, whereas A. platanoides ’ unusual combination of traits makes it invasive in both disturbed and undisturbed forests. Overall, native shade‐tolerant trees and slow stand dynamics make undisturbed forests highly resistant to invasion by exotic trees that are intolerant of shade. 6. Synthesis . This study showcases the importance of rapid growth in invasive plants, holding even for exotic tree species known to invade established forests. For A. altissima , high growth rates were accompanied by poor low‐light survivorship. A. platanoides departs from the general trade‐off pattern that exists among native species and A. altissima , and consequently it can be highly invasive in closed‐canopy forests.
Abstract. Repeated long-term censuses have revealed large-scale spatial patterns in Amazon basin forest structure and dynamism, with some forests in the west of the basin having up to a twice as high rate of aboveground biomass production and tree recruitment as forests in the east. Possible causes for this variation could be the climatic and edaphic gradients across the basin and/or the spatial distribution of tree species composition. To help understand causes of this variation a new individual-based model of tropical forest growth, designed to take full advantage of the forest census data available from the Amazonian Forest Inventory Network (RAINFOR), has been developed. The model allows for within-stand variations in tree size distribution and key functional traits and between-stand differences in climate and soil physical and chemical properties. It runs at the stand level with four functional traits – leaf dry mass per area (Ma), leaf nitrogen (NL) and phosphorus (PL) content and wood density (DW) varying from tree to tree – in a way that replicates the observed continua found within each stand. We first applied the model to validate canopy-level water fluxes at three eddy covariance flux measurement sites. For all three sites the canopy-level water fluxes were adequately simulated. We then applied the model at seven plots, where intensive measurements of carbon allocation are available. Tree-by-tree multi-annual growth rates generally agreed well with observations for small trees, but with deviations identified for larger trees. At the stand level, simulations at 40 plots were used to explore the influence of climate and soil nutrient availability on the gross (ΠG) and net (ΠN) primary production rates as well as the carbon use efficiency (CU). Simulated ΠG, ΠN and CU were not associated with temperature. On the other hand, all three measures of stand level productivity were positively related to both mean annual precipitation and soil nutrient status. Sensitivity studies showed a clear importance of an accurate parameterisation of within- and between-stand trait variability on the fidelity of model predictions. For example, when functional tree diversity was not included in the model (i.e. with just a single plant functional type with mean basin-wide trait values) the predictive ability of the model was reduced. This was also the case when basin-wide (as opposed to site-specific) trait distributions were applied within each stand. We conclude that models of tropical forest carbon, energy and water cycling should strive to accurately represent observed variations in functionally important traits across the range of relevant scales.
does not appear. First page follows. Introduction The relation of water to plant growth is of especial interest to growers of deciduous fruits. Consideration of the relative losses of moisture from irrigated soils by evaporation or transpiration through plants and by means of surface evaporation from the soil is becoming increasingly important. This is especially true in many of the deciduous fruit areas of California, where the cost of irrigation is one of the main items of expense in orchard management. The orchardist growing fruit in an arid or semi-arid region, where irrigation is necessary, supposedly has an advantage over the grower of similar fruit in a humid area, because the supply of moisture in the soil can be controlled to a greater extent. Therefore, it is important to consider the effect of different degrees of soil moisture on the use of water by trees, and the effect of such differences on the kind of fruit produced. A portion of the California deciduous fruit orchards have been planted in localities where dependence has been placed upon rainfall only. However that irrigation is necessary in many sections of California for the best production of horticultural crops is a fact now coming into recognition.
Predicting the student performance is playing vital role in educational sector so that the analysis of student's status helps to improve for better performance. Applying data mining concepts and algorithms in the field of education is Educational Data Mining. In recent days, Machine learning algorithms are very much useful in almost all the fields. Many researchers used machine learning algorithms only. In this paper we proposed the student performance prediction system using Deep Neural Network. We trained the model and tested with Kaggle dataset using different algorithms such as Decision Tree (C5.0), Na ve Bayes, Random Forest, Support Vector Machine, K-Nearest Neighbor and Deep neural network in R Programming and compared the accuracy of all other algorithms. Among six algorithms Deep Neural Network outperformed with 84% as accuracy.
As a tree grows taller, the increase in gravitational pressure and path length resistance results in lower water potentials at a given flow rate and higher carbon construction costs to transport a given amount of water to the leaves. We investigated how hydraulic safety and efficiency are coordinated under the constraints of higher cavitation risks and higher carbon construction costs with increasing tree height. We combined measurements of xylem tracheid anatomical traits with the vulnerability to drought-induced embolism and hydraulic conductivity of the apical shoots of 2- to 37-m tall Picea abies trees growing at two sites in the Dolomites (Italian Eastern Alps). We found that the theoretical hydraulic conductivity of the apical shoots increased with tree height at both sites (P < 0.001) as a result of an increase in either total tracheid number or mean hydraulic diameter. The xylem water potential inducing 50% loss of apical conductance significantly increased from small (-4.45 ± 0.20 MPa) to tall trees (-3.65 ± 0.03 MPa) (P = 0.007). The more conductive xylem at the treetop of taller trees allows the full compensation for the height-related hydraulic constraints and minimizes the additional carbon costs of transporting water over a longer path length. The corresponding increase in vulnerability to cavitation shows that hydraulic efficiency is prioritized over safety during height growth.
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Multi-agent pathfinding, where multiple agents must travel to their goal locations without getting stuck, has been studied in both theoretical and practical contexts, with a variety of both optimal and sub-optimal algorithms proposed for solving problems. Recent work has shown that there is a linear-time check for whether a multi-agent pathfinding problem can be solved in a tree, however this was not used to actually produce solutions. In this paper we provide a constructive proof of how to solve multi-agent pathfinding problems in a tree that culminates in a novel approach that we call the tree-based agent swapping strategy (TASS). Experimental results showed that TASS can find solutions to the multi-agent pathfinding problem on a highly crowded tree with 1000 nodes and 996 agents in less than 8 seconds. These results are far more efficient and general than existing work, suggesting that TASS is a productive line of study for multi-agent pathfinding.
Abstract: The sampling of epiphytes is fraught with methodological difficulties. We present a protocol to sample and analyse vascular epiphyte richness and abundance in forests of different structure (SVERA). Epiphyte abundance is estimated as biomass by recording the number of plant components in a range of size cohorts. Epiphyte species biomass is estimated on 35 sample-trees, evenly distributed over six trunk diameter-size cohorts (10 trees with dbh > 30 cm). Tree height, dbh and number of forks (diameter > 5 cm) yield a dimensionless estimate of the size of the tree. Epiphyte dry weight and species richness between forests is compared with ANCOVA that controls for tree size. S Chao1 is used as an estimate of the total number of species at the sites. The relative dependence of the distribution of the epiphyte communities on environmental and spatial variables may be assessed using multivariate analysis and Mantel test. In a case study, we compared epiphyte vegetation of six Mexican oak forests and one Colombian oak forest at similar elevation. We found a strongly significant positive correlation between tree size and epiphyte richness or biomass at all sites. In forests with a higher diversity of host trees, more trees must be sampled. Epiphyte biomass at the Colombian site was lower than in any of the Mexican sites; without correction for tree size no significant differences in terms of epiphyte biomass could be detected. The occurrence of spatial dependence, at both the landscape level and at the tree level, shows that the inclusion of spatial descriptors in SVERA is justified.
In Mediterranean environments in western North America, historic fire regimes in frequent-fire conifer forests are highly variable both temporally and spatially. This complexity influenced forest structure and spatial patterns, but some of this diversity has been lost due to anthropogenic disruption of ecosystem processes, including fire. Information from reference forest sites can help management efforts to restore forests conditions that may be more resilient to future changes in disturbance regimes and climate. In this study, we characterize tree spatial patterns using four-ha stem maps from four old-growth, Jeffrey pine-mixed conifer forests, two with active-fire regimes in northwestern Mexico and two that experienced fire exclusion in the southern Sierra Nevada. Most of the trees were in patches, averaging six to 11 trees per patch at 0.007 to 0.014 ha(-1), and occupied 27-46% of the study areas. Average canopy gap sizes (0.04 ha) covering 11-20% of the area were not significantly different among sites. The putative main effects of fire exclusion were higher densities of single trees in smaller size classes, larger proportion of trees (≥ 56%) in large patches (≥ 10 trees), and decreases in spatial complexity. While a homogenization of forest structure has been a typical result from fire exclusion, some similarities in patch, single tree, and gap attributes were maintained at these sites. These within-stand descriptions provide spatially relevant benchmarks from which to manage for structural heterogeneity in frequent-fire forest types.