Search Results (8)

Pinus radiata D. Don is planted in South Central Chile on a wide range of sites using genetically improved genotypes for timber production. As drought events are expected to increase with ongoing climatic change, the variability in gas exchange, which could impact growth and water use, needs to be evaluated. In this study, we assessed the genotypic variability of leaf-level light-saturated photosynthesis (A_sat), stomatal conductance (g_s), transpiration (E), intrinsic water use efficiency (iWUE), and Chlorophyll a fluorescence (OJIP-test parameters) among 30 P. radiata genotypes (i.e., full-sib families) from third-cycle parents at age 6 years on three sites in Central Chile. We also evaluated tree height (HT), diameter at breast height (DBH), and stem index volume (VOL). Families were ranked for HT as top-15 and bottom-15. In the OJIP-test parameters we observed differences at the family level for the maximum quantum yield of primary PSII photochemistry (Fv/Fm), the probability that a photon trapped by the PSII reaction center enters the electron transport chain (ψ_Eo), and the potential for energy conservation from photons captured by PSII to the reduction in intersystem electron acceptors (PI_ABS). Fv/Fm, PI_ABS, and ψ_Eo ranged from 0.82 to 0.87, 45 to 95, and 0.57 to 0.64, respectively. Differences among families for growth and not for leaf-level physiology were detected. DBT, H, and VOL were higher in the top-15 families (12.6 cm, 8.4 m, and 0.10 m³, respectively) whereas A_sat, g_s, E, and iWUE were similar in both the top-15 and bottom-15 families (4.0 μmol m⁻² s⁻¹, 0.023 mol m⁻² s⁻¹, 0.36 mmol m⁻² s⁻¹, and 185 μmol mol m⁻² s⁻¹, respectively). However, no family by site interaction was detected for growth and leaf-level physiology. The results of this study suggest that highly improved genotypes of P. radiata have uniformity in leaf-level physiological rates, which could imply uniform water use at the stand-level. The family variation found in PI_ABS suggests that this parameter could be incorporated to select genotypes tolerant to environmentally stressful conditions. Full article

The occurrence of short-interval, severe wildfires are increasing drastically at a global scale, and appear as a novel phenomenon in areas where fire historically returns in large time lapses. In forest ecosystems, these events induce drastic changes in population dynamics, which could dramatically impact species diversity. Here, we studied the effect on diversity of recent short-interval, severe wildfires (SISF), which occurred in rapid succession in the summers of 2002 and 2015 in Chilean Northern Patagonian Araucaria–Nothofagus forests. We analyzed the diversity of deadwood-dependent (i.e., saproxylic) and fire-sensitive beetles as biological indicators across four conditions: 2002-burned areas, 2015-burned areas, SISF areas (i.e., burned in 2002 and again in 2015), and unburned areas. Saproxylic beetles were collected using window traps in 2017 to 2019 summer seasons. To investigate the mechanisms underpinning the fire-related disturbance of the assemblage, we evaluated the effects of post-fire habitat quality (e.g., dead wood decomposition) and quantity (e.g., burned dead wood volume and tree density) on the abundances and species richness of the entire assemblage and also multiple trophic groups. Compared with the unburned condition, SISF drastically reduced species richness, evenness, and Shannon’s diversity and altered the composition of the saproxylic beetle assemblages. The between-condition variation in composition was accounted for by a species replacement (turnover) between SISF and 2015-burned areas, but both species replacement and extinction (nestedness) between SISF and unburned areas. Dead wood decomposition and tree density were the variables with the strongest effects on the abundance and species richness of the entire saproxylic beetle assemblage and most trophic groups. These results suggest that SISF, through degraded habitat quality (dead wood decomposition) and quantity (arboreal density), have detrimental impacts on diversity and population dynamics of saproxylic beetle assemblages. Therefore, habitat loss is a central mechanism underpinning fire-related biodiversity loss in these forest ecosystems. Full article

Ips cembrae is the most important bark beetle pest of larches and has had several local outbreaks in recent decades in Europe. In this study, we compared the numbers of I. cembrae captured by pyramid-trap piles, trap trees, pheromone traps, and poisoned and baited tripods. We also studied how the properties of trap trees and trap logs (volume, sun exposure, and position relative to the ground once deployed) affected the trapping of I. cembrae. We found that both sexes avoided infestation at the bottom of the logs and more than 15 times the number of beetles were captured by traditional trap trees than by pheromone traps or baited and insecticide-treated tripods. The number of I. cembrae per trap tree did not decrease with trap volume; therefore, it is appropriate to use traps of small dimensions. Baited tripods, pyramid-trap piles, and pheromone traps could be useful for detection of the beginning of flight activity, but trap trees are the most useful for reducing I. cembrae numbers. Full article

In liquid mediums, whether the breakdown strength can be greatly improved after introducing the nano-particles has been widely investigated, however, there has been no scientific consensus on the modification mechanism of this anomalous phenomenon. In this paper, we first experimentally measured the streamer morphology and breakdown strength in pure transformer oil, TiO${}_2$ nano-liquids and Al${}_2$O${}_3$ nano-liquids under microsecond pulse. The results demonstrated that there are significant differences in streamer morphology between pure transformer oil and nano-liquids, as the streamers in pure transformer oil exhibit thick bush-like qualities, while in nano-liquids they exhibit tree-like qualities. Moreover, the breakdown voltage results show that the breakdown strength of transformer oil is improved after nano-modification, and the TiO${}_2$ nano-liquids and Al${}_2$O${}_3$ nano-liquids have nearly the same optimal volume fraction. The results of the analysis indicate that the modification mechanism of nano-particles is significantly linked to the trapped electrons process. Specifically, the addition of nano-particles can affect the electrons’ density and thus affect the breakdown process and streamer morphology. Full article

Birch trees are abundant in central and northern Europe and are dominant trees in broadleaved forests. Birches are pioneer trees that produce large quantities of allergenic pollen efficiently dispersed by wind. The pollen load level depends on the sizes and locations of pollen sources, which are important for pollen forecasting models; however, very limited work has been done on this topic in comparison to research on anthropogenic air pollutants. Therefore, we used highly accurate aerial laser scanning (Light Detection and Ranging—LiDAR) data to estimate the size and location of birch pollen sources in 3-dimensional space and to determine their influence on the pollen concentration in Poznań, Poland. LiDAR data were acquired in May 2012. LiDAR point clouds were clipped to birch individuals (mapped in 2012–2014 and in 2019), normalised, filtered, and individual tree crowns higher than 5 m were delineated. Then, the crown surface and volume were calculated and aggregated according to wind direction up to 2 km from the pollen trap. Consistent with LIDAR data, hourly airborne pollen measurements (performed using a Hirst-type, 7-day volumetric trap), wind speed and direction data were obtained in April 2012. We delineated 18,740 birch trees, with an average density of 14.9/0.01 km², in the study area. The total birch crown surface in the 500–1500 m buffer from the pollen trap was significantly correlated with the pollen concentration aggregated by the wind direction (r = 0.728, p = 0.04). The individual tree crown delineation performed well (r² ≥ 0.89), but overestimations were observed at high birch densities (> 30 trees/plot). We showed that trees outside forests substantially contribute to the total pollen pool. We suggest that including the vertical dimension and the trees outside the forest in pollen source maps have the potential to improve the quality of pollen forecasting models. Full article

Modern agriculture requires technology to give precise measures about relevant parameters such as pest control. Here, we developed a decision support system (DSS) based on semi-automatic pest monitoring for managing the olive fruit fly Bactrocera oleae (Rossi), in Mallorca (Balearic Islands, Spain). The DSS was based on an algorithm that took into account spatial and temporal patterns of olive fruit fly population in an orchard where all trees were georeferenced, thus precise treatments against the pest were conducted through a location aware system (LAS). The olive fruit fly adult population was monitored by using ad hoc off-the-grid autonomous electronic traps.The results were compared with those obtained with conventional methods. For a pilot trial, we selected an olive-producing orchard, where from June to October 2015, three plots using LAS management and three plots under conventional control (NO-LAS plots) were compared. Spray threshold considered both adult population and fruit damage. An additional non-sprayed plot was selected for assessing biological control due to the parasitoid, Psyttalia concolor (Szépligeti). Results showed that the use of DSS reduced by 36.84% the volume of insecticide used in LAS compared to NO-LAS plots. Accordingly, time and distance needed for spraying were also reduced. Adult olive fruit fly population was lower in the LAS plots when compared with the NO-LAS plots; conversely, fruit infestation was higher in LAS compared with NO-LAS. The implementation of LAS and DSS at field level allowed real-time monitoring of adult olive flies, thereby increasing the accuracy and precision of sprays in time and space and decreasing impact on natural enemies. Full article

Two diseases, Rhabdocline needle cast caused by Rhabdocline pseudotsugae Sydow, and Swiss needle cast caused by Phaeocryptopus gaeumannii (Rohde) Petr., recently became a severe threat to Central European Douglas fir (Pseudotsuga menziesii (Mirb.) Franco) stands. Both pathogens infect assimilative organs causing needle chloritization and drop off. Pervasive infection by these pathogens has been recorded at the Hůrky provenance trial (Písek, South Bohemia, Czech Republic), established in 1971 as part of a series of experiments by International Union of Forest Research Organizations (IUFRO). The intensity and duration of needle cast sporulation were monitored using a Burkard spore trap, and the health status of 24 Douglas fir provenances from the original areal of distribution (British Columbia, Washington, Oregon) was evaluated under this trial. While comparing provenances, the following characteristics were surveyed: trunk volume, defoliation rate, and the difference in tree diameter between measurements in 2011 and 2016. A statistical evaluation was performed using the regression model and a decision tree. The highest sporulation rates on needles for both needle casts were observed from April to July. The Washington provenances 1069 North Bend, 1075 Enumclaw, and 1089 Cathlamet can be recommended for plantation, considering the provenances’ satisfactory productivity and low extent of damage from needle casts, while the provenances such as 1104 Brookings, 1028 Merritt (due to high mortality) and 1010 Barrière, 1021 D’Arcy, and 1067 Skykomish (due to high defoliation) are not suitable for plantation under Central European conditions. Full article

Modern agriculture is facing unique challenges in building a sustainable future for food production, in which the reliable detection of plantation threats is of critical importance. The breadth of existing information sources, and their equivalent sensors, can provide a wealth of data which, to be useful, must be transformed into actionable knowledge. Approaches based on Information Communication Technologies (ICT) have been shown to be able to help farmers and related stakeholders make decisions on problems by examining large volumes of data while assessing multiple criteria. In this paper, we address the automated identification (and count the instances) of the major threat of olive trees and their fruit, the Bactrocera Oleae (a.k.a. Dacus) based on images of the commonly used McPhail trap’s contents. Accordingly, we introduce the “Dacus Image Recognition Toolkit” (DIRT), a collection of publicly available data, programming code samples and web-services focused at supporting research aiming at the management the Dacus as well as extensive experimentation on the capability of the proposed dataset in identifying Dacuses using Deep Learning methods. Experimental results indicated performance accuracy (mAP) of 91.52% in identifying Dacuses in trap images featuring various pests. Moreover, the results also indicated a trade-off between image attributes affecting detail, file size and complexity of approaches and mAP performance that can be selectively used to better tackle the needs of each usage scenario. Full article