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The mahogany shoot borer, Hypsipyla grandella Zeller (Lepidoptera: Pyralidae), is one of the most economically important pests in all American tropical forests because it prevents the establishment of monoculture plantations of the family Meliaceae, such as Spanish cedar, Cedrela odorata L. Various studies have focussed on the bioecological aspects and the chemical and silvicultural control of this pest. However, relatively little is known about the biological interactions between this insect and its host plant. In this study, the shoot borer's behavior and attraction response to cedar host plants was evaluated in field cages. We also identified the volatiles emitted by healthy C. odorata plants that were attractive to H. grandella adults. The attraction to headspace volatiles from cedar plants and a synthetic blend were evaluated in a Y-glass tube olfactometer. We observed that virgin and mated females exhibited low activity at night, frequent movement of the antennae, sporadic flight activity, and short (< 10 s) and long (> 30 s) wing-fanning. Virgin females assumed a calling position, whereas mated females exhibited three periods of oviposition. The results showed that all evaluated categories – virgin females, virgin males, and mated females – were attracted to cedar plants. We identified the following volatile compounds: α-pinene, (E)-β-ocimene, 2-ethyl-1-hexanol, limonene, nonanal, (E)-4,8-dimethyl-1,3,7-nonatriene, α-copaene, β-caryophyllene, and germacrene D. A synthetic blend significantly attracted virgin male and mated female shoot borers. Our results suggested that C. odorata volatiles compounds are responsible for the attraction of H. grandella.

Tree ring analysis allows reconstructing historical growth rates over long periods. Several studies have reported an increasing trend in ring widths, often attributed to growth stimulation by increasing atmospheric CO2 concentration. However, these trends may also have been caused by sampling biases. Here we describe two biases and evaluate their magnitude. (1) The slow-grower survivorship bias is caused by differences in tree longevity of fast- and slow-growing trees within a population. If fast-growing trees live shorter, they are underrepresented in the ancient portion of the tree ring data set. As a result, reconstructed growth rates in the distant past are biased toward slower growth. (2) The big-tree selection bias is caused by sampling only the biggest trees in a population. As a result, slow-growing small trees are underrepresented in recent times as they did not reach the minimum sample diameter. We constructed stochastic models to simulate growth trajectories based on a hypothetical species with lifetime constant growth rates and on observed tree ring data from the tropical tree Cedrela odorata. Tree growth rates used as input in our models were kept constant over time. By mimicking a standard tree ring sampling approach and selecting only big living trees, we show that both biases lead to apparent increases in historical growth rates. Increases for the slow-grower survivorship bias were relatively small and depended strongly on assumptions about tree mortality. The big-tree selection bias resulted in strong historical increases, with a doubling in growth rates over recent decades. A literature review suggests that historical growth increases reported in many tree ring studies may have been partially due to the big-tree sampling bias. We call for great caution in the interpretation of historical growth trends from tree ring analyses and recommend that such studies include individuals of all sizes.

Background The current state-of-the-art for field wood identification to combat illegal logging relies on experienced practitioners using hand lenses, specialized identification keys, atlases of woods, and field manuals. Accumulation of this expertise is time-consuming and access to training is relatively rare compared to the international demand for field wood identification. A reliable, consistent and cost effective field screening method is necessary for effective global scale enforcement of international treaties such as the Convention on the International Trade in Endagered Species (CITES) or national laws (e.g. the US Lacey Act) governing timber trade and imports. Results We present highly effective computer vision classification models, based on deep convolutional neural networks, trained via transfer learning, to identify the woods of 10 neotropical species in the family Meliaceae, including CITES-listed Swietenia macrophylla , Swietenia mahagoni , Cedrela fissilis , and Cedrela odorata . We build and evaluate models to classify the 10 woods at the species and genus levels, with image-level model accuracy ranging from 87.4 to 97.5%, with the strongest performance by the genus-level model. Misclassified images are attributed to classes consistent with traditional wood anatomical results, and our species-level accuracy greatly exceeds the resolution of traditional wood identification. Conclusion The end-to-end trained image classifiers that we present discriminate the woods based on digital images of the transverse surface of solid wood blocks, which are surfaces and images that can be prepared and captured in the field. Hence this work represents a strong proof-of-concept for using computer vision and convolutional neural networks to develop practical models for field screening timber and wood products to combat illegal logging.

We present a unique proxy for the reconstruction of variation in precipitation over the Amazon: oxygen isotope ratios in annual rings in tropical cedar (Cedrela odorata). A century-long record from northern Bolivia shows that tree rings preserve the signal of oxygen isotopes in precipitation during the wet season, with weaker influences of temperature and vapor pressure. Tree ring δ ¹⁸O correlates strongly with δ ¹⁸O in precipitation from distant stations in the center and west of the basin, and with Andean ice core δ ¹⁸O showing that the signal is coherent over large areas. The signal correlates most strongly with basin-wide precipitation and Amazon river discharge. We attribute the strength of this (negative) correlation mainly to the cumulative rainout processes of oxygen isotopes (Rayleigh distillation) in air parcels during westward transport across the basin. We further find a clear signature of the El Niño-Southern Oscillation (ENSO) in the record, with strong ENSO influences over recent decades, but weaker influence from 1925 to 1975 indicating decadal scale variation in the controls on the hydrological cycle. The record exhibits a significant increase in δ ¹⁸O over the 20th century consistent with increases in Andean δ ¹⁸O ice core and lake records, which we tentatively attribute to increased water vapor transport into the basin. Taking these data together, our record reveals a fresh path to diagnose and improve our understanding of variation and trends of the hydrological cycle of the world’s largest river catchment.

This study reports the green synthesis and characterization of silver nanoparticles (AgNPs) assisted with Cedrela odorata extracts and their antifungal efficacy against Fusarium circinatum, one of the most threatening pathogens in forest nurseries. Various extract volumes (1, 3, and 5 mL) of leaf and the bark of red cedar were tested. The nanoparticles were characterized using UV-Vis spectroscopy, transmission electron microscopy, and energy-dispersive spectroscopy of X-rays (EDS-TEM). Phytochemicals in the extracts were explored using Fourier transform infrared spectroscopy (FTIR). The results were analyzed using ANOVA and Tukey’s tests with (p ≤ 0.05, 95%). Both leaves and bark extracts produced AgNPs, but the particles from bark extract (AgNPs-B) were smaller (19.80 ± 9.88 nm, λmax at 447 nm), and they were more stable than particles from leaf extract (AgNPs-L) because they showed a superficial plasmon resonance (SPR) over 12 months. Phenols and triterpenoids, associated with -OH, C=O, and –NH, were identified in the plant extracts that could act as reducing and capping agents. The AgNPs exhibited good antifungal activity because the inhibition diameter (11.38 ± 0.8 mm) observed for 800 mg AgNO3 L−1 was statistically similar to the inhibition diameter (10.7 ± 0.7 mm) at lower concentrations of particles (200 mg AgNPs L−1), and benzimidazole showed no fungus inhibition. Hence, it could be concluded that the bark extract performed better than the leaf extract. In conclusion, this study reports a new method for the synthesis of AgNPs assisted with cedar bark that exhibit a good antifungal activity against F. circinatum.

The roots of different forest species show mixed colonization by arbuscular mycorrhizal fungi (AMF) and dark septate fungi (DSE). In temperate ecosystems, AMF colonization and community structure change according to plantation age, while colonization by DSE is apparently unaffected. However, in tropical ecosystems, little has been documented on the possible changes caused by plantation age on mycorrhizal fungal communities. We analyzed AMF and DSE colonization and described the glomerospore community structure associated with three agroforestry systems of different Cedrela odorata plantation ages (8, 13 and 17 years), in addition to a secondary forest, during the dry season in southeastern Costa Rica. We detected statistical differences in total colonization in the agroforestry systems with respect to the secondary forest (P < 0.05). Among the agroforestry systems, total colonization was higher in 8-year-old trees and DSE were only detected in agroforestry systems with higher colonization in 8-year-old trees. The abundance and richness of glomerospores were higher in the agroforestry systems than in the secondary forest, with greater richness in younger plantations. We isolated 39 morphospecies, 27 from the plantations and 17 from the secondary forest, with a greater representativeness of Acaulospora and Glomus. We also provide four new AMF reports for Costa Rica (Acaulospora laevis, A. excavata, A. spinosissima, and A. bireticulata).

Most of the West African forests have disappeared or have been deeply fragmented. This deforestation dynamic is still ongoing under a strong demographic pressure, forests being mostly replaced by agricultural lands. On the other hand, some reforestation projects are also undertaken, in particular by planting non-native species like Cedrela odorata. To our knowledge, this study is the first to investigate the causes and consequences of Cedrela odorata spread in West African natural forests. We studied a 400ha area of natural forest where 100ha of permanent plots have been affected by a major fire in 1983. Within these permanent plots, 21,444 trees were mapped, botanically determined and their diameters at breast height were measured in 2018. Using a bayesian hierarchical framework, we modelled the causes of the spread of Cedrela odorata in the studied plots, and its consequences on aboveground biomass and tree community diversity. Regarding the causes, the occurrence of Cedrela odorata is significantly linked to the fire occurence 25 years ago, to the proximity of the forest edge and to the presence of hydromorphic soils. Regarding the consequences, Cedrela odorata invasion doesn’t have any significant impact on the above-ground biomass but has a strong negative effect on the tree community diversity, as far as decreasing Simpson diversity in Hill numbers from 27 equivalent species in slightly invaded plots to 2 equivalent species in largely invaded plots. Our results highlight the long-lasting impacts of human disturbance (fire, Cedrela odorata introduction) on forest ecosystems and the need to use local species for ongoing reforestation plans in West African semi-deciduous forests.

The last remnants of lowland forests in eastern Africa are biodiversity hotspots as they host a unique set of endemic animal and plant species. However, the diversity of the forests is threatened by man-made disturbances, including the introduction of non-native plant species. Here, we assessed the current extent and drivers of the spread of the invasive neotropical tree, Cedrela odorata L., introduced to Kimboza Forest Reserve in 1957 and 1960. We also assessed the impacts of the invasion on the composition of native tree recruitment (height < 0.5 m). The extent of invasion and drivers was assessed in 107 square plots (10 × 10 m) and 240 subplots (2 × 2 m) distributed systematically throughout the forest. The impact of C. odorata was assessed in 24 paired square sample plots (10 × 10 m) that were established in forest patches invaded and uninvaded by C. odorata. By 2017, adult C. odorata trees (diameter at breast height (DBH) ≥ 10 cm) occurred in 43% of plots and comprised, on average, 32% of the stems of all tree species and 28% of the basal area. The occurrence of C. odorata in the forest was significantly associated with the occurrences of wildfire and illegal logging, and significantly affected the density of native tree recruitments, Sorindeia madagascariensis and Rinorea arborea but did not affect the species diversity. Management actions are needed to reduce the negative impacts of invaded forest patches and prevent the uninvaded forest patches from invasion.

Invasive plants are one of the greatest threats leading to biodiversity loss and species extinction worldwide. Understanding the responses of liana and tree communities as well as liana-tree interactions to plant invasion could be important in biodiversity conservation and ecosystem functioning, but there is limited knowledge on this subject matter. We therefore sought to determine how the diversity, composition and structure of native liana and tree communities and liana-tree interaction networks responded to invasion by three tree species (Broussonetia papyrifera¸ Cedrela odorata, Tectona grandis) in two moist semi-deciduous forests in Ghana. Effects of plant invasion on native liana and tree community structure and liana-tree network structure were quantified by sampling liana species with diameter at 1.30 m from rooting base  ≥ 1 cm, and tree species with diameter at breast height ≥ 5 cm in 20 20 × 20 m plots each in non-invaded and invaded sites. The findings of the study showed that plant invasion was associated with lower diversity and abundance of lianas and trees as well as shifts in species composition of the plants. Our results revealed that plant invasion influenced the patterns of liana-tree network structure, and tended to cause an increase in network connectance and nestedness, and a decrease in network modularity and specialisation. Plant invasion drove the topological roles of a few liana and tree species in the invaded sites. Generally, species abundance and specificity were important correlates of nestedness, and modularity and species roles of the networks. We conclude that the invasive tree species drove native liana and tree community structure, degree of liana-tree network structure, and species topological roles, all of which may have adverse consequences on biodiversity in the forests.

Rainfall and river levels in the Amazon are associated with significant precipitation anomalies of opposite sign in temperate North and South America, which is the dominant mode of precipitation variability in the Americas that often arises during extremes of the El Niño/Southern Oscillation (ENSO). This co-variability of precipitation extremes across the Americas is imprinted on tree growth and is detected when new tree-ring chronologies from the eastern equatorial Amazon are compared with hundreds of moisture-sensitive tree-ring chronologies in mid-latitude North and South America from 1759 to 2016. Pan-American co-variability exists even though the seasonality of precipitation and tree growth only partially overlaps between the Amazon and mid-latitudes because ENSO forcing of climate can persist for multiple seasons and can orchestrate a coherent response, even where the growing seasons are not fully synchronized. The tree-ring data indicate that the El Niño influence on inter-hemispheric precipitation and tree growth extremes has been strong and stable over the past 258-years, but the La Niña influence has been subject to large multi-decadal changes. These changes have implications for the dynamics and forecasting of hydroclimatic variability over the Americas and are supported by analyses of the available instrumental data and selected climate model simulations.