943 resultados para honey-tree species


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Predatory mites (Acari: Mesostigmata) on tree trunks without significant epiphytic growth in a subtropical rainforest in Eastern Australia were assessed for habitat specificity (i.e. whether they are tree trunk specialists or occupying other habitats) and the influence of host tree and bark structure on their abundance, species richness and species composition. The trunks of nine tree species from eight plant families representing smooth, intermediate and rough bark textures were sampled using a knockdown insecticide spray. In total, 12 species or morphospecies of Mesostigmata (excluding Uropodina sensu stricto) were collected, most of which are undescribed. Comparison with collections from other habitats indicates that epicorticolous Mesostigmata are mainly represented by suspended soil dwellers (six species), secondarily by generalists (four species) and a bark specialist (one species). A typical ground-dwelling species was also found but was represented only by a single individual. In terms of abundance, 50.5% of individuals were suspended soil dwellers, 40.7% bark specialists, and 8.3% generalists. Host species and bark roughness had no significant effect on abundance or species richness. Furthermore, there was no clear effect on species composition. The distribution of the most frequently encountered species suggests that most mesostigmatid mites living on bark use many or most rainforest tree species, independent of bark roughness. These findings support the hypothesis that some epicorticolous Mesostigmata use tree trunks as 'highways' for dispersing between habitat patches, while others use it as a permanent habitat.

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The performance of 32 tropical rainforest and eucalypt tree species grown in private, mixed species plantations was examined. There were two objectives: 1) to summarise the growth of species by soil and rainfall classes, 2) to investigate the degree of variability in growth rates with respect to environmental variables. Data were collected from 112 plots established in the Community Rainforest Reforestation Program (CRRP) plantations across sites in the humid tropics of central and north Queensland. Sites ranged from sea level to 1160 m above sea level, with annual rainfall from 800 mm to 4300 mm, on soils derived from basalt, metamorphic and granite parent material. Species performance was significantly related to climatic and edaphic variables but the strength of these relationships differed among taxa.

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Understanding how climate change will affect the distribution and the phenology of plants is becoming an increasingly important topic in ecological studies. In response to climate warming, there are documented upward shift and alterations of phenology and physiology of several plant species. Despite this, the effects of climate change on plant regeneration from seeds have largely been neglected. However, regeneration from seeds, a key event in the plant life cycle, could be significantly affected by climate warming. In this regard, we investigated how climatic changes will affect the seasonal dynamics of seed germination and seedling survival in two different alpine context. The first part refers to five species inhabiting a snowbed located at the Gavia pass (Parco Naturale dello Stelvio). Here, plants were exposed, in the field, to natural conditions and to artificial warming using Open Top Chambers proposed by the ITEX (International Tundra Experiment). The germination curves of seeds produced were compared in order to highlight differences in seed germination ecology and in seed physiology induced by the climate warming. In the second part, we considered two tree species that form the treeline in Davos (Switzerland). As a surrogate of climate warming we used the natural thermal gradient driven by the altitude and we compared the germination behavior of the species studied in three sites at three different elevations in order to evaluate the likelihood of treeline shift under the predicted climate warming.

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The subtropical hardwood forests of southern Florida are formed by 120 frost-sensitive, broadleaved angiosperm species that range throughout the Caribbean. Previous work on a series of small sized forest component patches of a 20 km2, forest preserve in northern Key Largo indicate that a shift in species composition was associated with a 100 year forest developmental sequence, and this shift was associated with an increasingly evergreen canopy. This document investigates the underlying differences of the biology of trees that live in this habitat, and is specifically focused on the impact of leaf morphology on changing nutrient cycling patterns. Measurements of the area, thickness, dry mass, nutrient content and longevity of several leaves from 3-4 individuals of ten species were conducted in combination with a two-year leaf litter collection and nutrient analysis to determine that species with thicker, denser leaves cycled scarce nutrients up to 2-3 times more efficiently than thin leaved tree species, and the leaf thickness/density index predicts role in forest development in a parallel direction as the index predicts nutrient cycling efficiency. A three year set of observations on the relative abundance of new leaves, flowers and fruits of the same tree species provides an opportunity to evaluate the consequences the leaf morphology/nutrient cycling/forest development relationship to forest habitat quality. Results of the three documents support a mechanistic link between forest development and nutrient cycling, and suggests that older forests are likely to be better habitats based on the availability of valuable forest products like new leaves, flowers, and fruits throughout the year.

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Recently, evapotranspiration has been hypothesized to promote the secondary formation of calcium carbonate year-round on tree islands in the Everglades by influencing groundwater ions concentrations. However, the role of recharge and evapotranspiration as drivers of shallow groundwater ion accumulation has not been investigated. The goal of this study is to develop a hydrologic model that predicts the chloride concentrations of shallow tree island groundwater and to determine the influence of overlying biomass and underlying geologic material on these concentrations. Groundwater and surface water levels and chloride concentrations were monitored on eight constructed tree islands at the Loxahatchee Impoundment Landscape Assessment (LILA) from 2007 to 2010. The tree islands at LILA were constructed predominately of peat, or of peat and limestone, and were planted with saplings of native tree species in 2006 and 2007. The model predicted low shallow groundwater chloride concentrations when inputs of regional groundwater and evapotranspiration-to-recharge rates were elevated, while low evapotranspiration-to-recharge rates resulted in a substantial increase of the chloride concentrations of the shallow groundwater. Modeling results indicated that evapotranspiration typically exceeded recharge on the older tree islands and those with a limestone lithology, which resulted in greater inputs of regional groundwater. A sensitivity analysis indicated the shallow groundwater chloride concentrations were most sensitive to alterations in specific yield during the wet season and hydraulic conductivity in the dry season. In conclusion, the inputs of rainfall, underlying hydrologic properties of tree islands sediments and forest structure may explain the variation in ion concentration seen across Everglades tree islands.

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Tree islands are an important structural component of many graminoid-dominated wetlands because they increase ecological complexity in the landscape. Tree island area has been drastically reduced with hydrologic modifications within the Everglades ecosystem, yet still little is known about the ecosystem ecology of Everglades tree islands. As part of an ongoing study to investigate the effects of hydrologic restoration on short hydroperiod marshes of the southern Everglades, we report an ecosystem characterization of seasonally flooded tree islands relative to locations described by variation in freshwater flow (i.e. locally enhanced freshwater flow by levee removal). We quantified: (1) forest structure, litterfall production, nutrient utilization, soil dynamics, and hydrologic properties of six tree islands and (2) soil and surface water physico-chemical properties of adjacent marshes. Tree islands efficiently utilized both phosphorus and nitrogen, but indices of nutrient-use efficiency indicated stronger P than N limitation. Tree islands were distinct in structure and biogeochemical properties from the surrounding marsh, maintaining higher organically bound P and N, but lower inorganic N. Annual variation resulting in increased hydroperiod and lower wet season water levels not only increased nitrogen use by tree species and decreased N:P values of the dominant plant species (Chrysobalanus icaco), but also increased soil pH and decreased soil temperature. When compared with other forested wetlands, these Everglades tree islands were among the most nutrient efficient, likely a function of nutrient immobilization in soils and the calcium carbonate bedrock. Tree islands of our study area are defined by: (1) unique biogeochemical properties when compared with adjacent short hydroperiod marshes and other forested wetlands and (2) an intricate relationship with marsh hydrology. As such, they may play an important and disproportionate role in nutrient and carbon cycling in Everglades wetlands. With the loss of tree islands that has occurred with the degradation of the Everglades system, these landscape processes may have been altered. With this baseline dataset, we have established a long-term ecosystem-scale experiment to follow the ecosystem trajectory of seasonally flooded tree islands in response to hydrologic restoration of the southern Everglades.

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Recently, evapotranspiration has been hypothesized to promote the secondary formation of calcium carbonate year-round on tree islands in the Everglades by influencing groundwater ions concentrations. However, the role of recharge and evapotranspiration as drivers of shallow groundwater ion accumulation has not been investigated. The goal of this study is to develop a hydrologic model that predicts the chloride concentrations of shallow tree island groundwater and to determine the influence of overlying biomass and underlying geologic material on these concentrations. Groundwater and surface water levels and chloride concentrations were monitored on eight constructed tree islands at the Loxahatchee Impoundment Landscape Assessment (LILA) from 2007 to 2010. The tree islands at LILA were constructed predominately of peat, or of peat and limestone, and were planted with saplings of native tree species in 2006 and 2007. The model predicted low shallow groundwater chloride concentrations when inputs of regional groundwater and evapotranspiration-to-recharge rates were elevated, while low evapotranspiration-to-recharge rates resulted in a substantial increase of the chloride concentrations of the shallow groundwater. Modeling results indicated that evapotranspiration typically exceeded recharge on the older tree islands and those with a limestone lithology, which resulted in greater inputs of regional groundwater. A sensitivity analysis indicated the shallow groundwater chloride concentrations were most sensitive to alterations in specific yield during the wet season and hydraulic conductivity in the dry season. In conclusion, the inputs of rainfall, underlying hydrologic properties of tree islands sediments and forest structure may explain the variation in ion concentration seen across Everglades tree islands.

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In 2005 we initiated a project designed to better understand tree island structure and function in the Everglades and the wetlands bordering it. Focus was on the raised portions at the upstream end of the islands, where tropical hardwood species adapted to well-drained conditions usually are the most prominent component of the vegetation. The study design is hierarchical, with four levels; in general, a large number of sites is to be surveyed once for a limited set of parameters, and increasingly small sets of islands are to be sampled more intensively, more frequently, and for more aspects of ecosystem function. During the first year of the 3-year study, we completed surveys of 41 Level 1 (i.e., the least intensive level) islands, and established permanent plots in two and three islands of Levels 2 and 4 intensity, respectively. Tree species richness and structural complexity was highest in Shark Slough “hammocks”, while islands in Northeast Shark Slough and Water Conservation Area 3B, which receive heavy human use, were simpler, more park-like communities. Initial monitoring of soil moisture in Level 4 hammocks indicated considerable local variation, presumably associated with antecedent rainfall and current water levels in the adjacent marsh. Tree islands throughout the study area were impacted significantly by Hurricanes Katrina and Wilma in 2005, but appear to be recovering rapidly. As the project continues to include more islands and repeated measurements, we expect to develop a better grasp of tree island dynamics across the Everglades ecosystem, especially with respect to moisture relations and water levels in the adjacent marsh. The detailed progress report which follows is also available online at http://www.fiu.edu/~serp1/projects/treeislands/tree_islands_2005_annual_report.pd

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This study examined how different rainfall regimes affect a set of leaf functional traits related to plant stress and forest structure in tropical dry forest (TDF) species on limestone substrate. One hundred fifty eight individuals of four tree species were sampled in six ecological sites in south Florida and Puerto Rico, ranging in mean annual rainfall from 858 to 1933 mm yr-1. Leaf nitrogen content, specific leaf area (SLA), and N:P ratio of evergreen species, but not deciduous species, responded positively to increasing rainfall. Phosphorus content was unaffected in both groups. Canopy height and basal area reached maxima of 10.3 m and 31.4 m2 ha-1, respectively, at 1168 mm annual rainfall. Leaf traits reflected soil properties only to a small extent. This led us to the conclusion that water is a major limiting factor in TDF and some species that comprise TDF ecosystems are limited by nitrogen in limestone sites with less than ~1012 mm rainfall, but organismal, biological and/or abiotic forces other than rainfall control forest structure in moister sites.

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Morphological, anatomical and physiological plant and leaf traits of A. distorta, an endemic species of the Central Apennines on the Majella Massif, growing at 2,675 m a.s.l, were analyzed. The length of the phenological cycle starts immediately after the snowmelt at the end of May, lasting 128 ± 10 days. The low A. distorta height  (Hmax= 64 ± 4 mm) and total leaf area (TLA= 38 ± 9 cm2) associated to a high leaf mass area (LMA =11.8±0.6 mg cm−2) and a relatively high leaf tissue density (LTD = 124.6±14.3 mg cm−3) seem to be adaptive traits to the stress factors of the environment where it grows. From a physiological point of view, the high A. distorta photosynthetic rates (PN =19.6 ± 2.3 µmol m−2 s−1) and total chlorophyll content (Chla+b = 0.88 ± 0.13 mg g−1) in July are justified by the favorable temperature. PN decreases by 87% in September at the beginning of plant senescence. Photosynthesis and leaf respiration (RD) variations allow A. distorta to maintain a positive carbon balance during the growing season becoming indicative of the efficiency of plant carbon use. The results could be an important tool for conservation programmes of the A. distorta wild populations.

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In the last decade, research in Computer Vision has developed several algorithms to help botanists and non-experts to classify plants based on images of their leaves. LeafSnap is a mobile application that uses a multiscale curvature model of the leaf margin to classify leaf images into species. It has achieved high levels of accuracy on 184 tree species from Northeast US. We extend the research that led to the development of LeafSnap along two lines. First, LeafSnap’s underlying algorithms are applied to a set of 66 tree species from Costa Rica. Then, texture is used as an additional criterion to measure the level of improvement achieved in the automatic identification of Costa Rica tree species. A 25.6% improvement was achieved for a Costa Rican clean image dataset and 42.5% for a Costa Rican noisy image dataset. In both cases, our results show this increment as statistically significant. Further statistical analysis of visual noise impact, best algorithm combinations per species, and best value of k , the minimal cardinality of the set of candidate species that the tested algorithms render as best matches is also presented in this research

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Forest trees, like oaks, rely on high levels of genetic variation to adapt to varying environmental conditions. Thus, genetic variation and its distribution are important for the long-term survival and adaptability of oak populations. Climate change is projected to lead to increased drought and fire events as well as a northward migration of tree species, including oaks. Additionally, decline in oak regeneration has become increasingly concerning since it may lead to decreased gene flow and increased inbreeding levels. This will in turn lead to lowered levels of genetic diversity, negatively affecting the growth and survival of populations. At the same time, populations at the species’ distribution edge, like those in this study, could possess important stores of genetic diversity and adaptive potential, while also being vulnerable to climatic or anthropogenic changes. A survey of the level and distribution of genetic variation and identification of potentially adaptive genes is needed since adaptive genetic variation is essential for their long-term survival. Oaks possess a remarkable characteristic in that they maintain their species identity and specific environmental adaptations despite their propensity to hybridize. Thus, in the face of interspecific gene flow, some areas of the genome remain differentiated due to selection. This characteristic allows the study of local environmental adaptation through genetic variation analyses. Furthermore, using genic markers with known putative functions makes it possible to link those differentiated markers to potential adaptive traits (e.g., flowering time, drought stress tolerance). Demographic processes like gene flow and genetic drift also play an important role in how genes (including adaptive genes) are maintained or spread. These processes are influenced by disturbances, both natural and anthropogenic. An examination of how genetic variation is geographically distributed can display how these genetic processes and geographical disturbances influence genetic variation patterns. For example, the spatial clustering of closely related trees could promote inbreeding with associated negative effects (inbreeding depression), if gene flow is limited. In turn this can have negative consequences for a species’ ability to adapt to changing environmental conditions. In contrast, interspecific hybridization may also allow the transfer of genes between species that increase their adaptive potential in a changing environment. I have studied the ecologically divergent, interfertile red oaks, Quercus rubra and Q. ellipsoidalis, to identify genes with potential roles in adaptation to abiotic stress through traits such as drought tolerance and flowering time, and to assess the level and distribution of genetic variation. I found evidence for moderate gene flow between the two species and low interspecific genetic differences at most genetic markers (Lind and Gailing 2013). However, the screening of genic markers with potential roles in phenology and drought tolerance led to the identification of a CONSTANS-like (COL) gene, a candidate gene for flowering time and growth. This marker, located in the coding region of the gene, was highly differentiated between the two species in multiple geographical areas, despite interspecific gene flow, and may play a role in reproductive isolation and adaptive divergence between the two species (Lind-Riehl et al. 2014). Since climate change could result in a northward migration of trees species like oaks, this gene could be important in maintaining species identity despite increased contact zones between species (e.g., increased gene flow). Finally I examined differences in spatial genetic structure (SGS) and genetic variation between species and populations subjected to different management strategies and natural disturbances. Diverse management activities combined with various natural disturbances as well as species specific life history traits influenced SGS patterns and inbreeding levels (Lind-Riehl and Gailing submitted).

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Knowledge of the geographical distribution of timber tree species in the Amazon is still scarce. This is especially true at the local level, thereby limiting natural resource management actions. Forest inventories are key sources of information on the occurrence of such species. However, areas with approved forest management plans are mostly located near access roads and the main industrial centers. The present study aimed to assess the spatial scale effects of forest inventories used as sources of occurrence data in the interpolation of potential species distribution models. The occurrence data of a group of six forest tree species were divided into four geographical areas during the modeling process. Several sampling schemes were then tested applying the maximum entropy algorithm, using the following predictor variables: elevation, slope, exposure, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). The results revealed that using occurrence data from only one geographical area with unique environmental characteristics increased both model overfitting to input data and omission error rates. The use of a diagonal systematic sampling scheme and lower threshold values led to improved model performance. Forest inventories may be used to predict areas with a high probability of species occurrence, provided they are located in forest management plan regions representative of the environmental range of the model projection area.

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This paper reports on the empirical comparison of seven machine learning algorithms in texture classification with application to vegetation management in power line corridors. Aiming at classifying tree species in power line corridors, object-based method is employed. Individual tree crowns are segmented as the basic classification units and three classic texture features are extracted as the input to the classification algorithms. Several widely used performance metrics are used to evaluate the classification algorithms. The experimental results demonstrate that the classification performance depends on the performance matrix, the characteristics of datasets and the feature used.