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Successfully separating wood and leaves in forest plots is a prerequisite for measuring structural parameters and reconstructing 3D forest models. Terrestrial laser scanning (TLS) can distinguish between the leaves and wood of trees through precise and dense point clouds. However, most existing wood–leaf separation methods face significant accuracy issues, especially in dense forests, due to the complications introduced by canopy shading. In this study, we propose a method to separate the wood and leaves in forest plots using the clustering features of TLS data. The method first filters a point cloud to remove the ground points, and then clusters the point cloud using a region-growing algorithm. Next, the clusters are processed based on their sizes and numbers of points for preliminary separation. Chaos Distance is introduced to characterize the observation that wood points are more orderly while leaf points are more chaotic and disorganized. Lastly, the clusters' Chaos Distance is used for the final separation. Three representative plots were used to validate this method, achieving an average accuracy of 0.938, a precision of 0.927, a recall of 0.892, and an F1 score of 0.907. The three sample plots were processed in 5.18, 3.75, and 14.52 min, demonstrating high efficiency. Comparing the results with the LeWoS and RF models showed that our method better addresses the accuracy issues of complex canopy structures. [ABSTRACT FROM AUTHOR]

Ecology needs a unified view of the patterns and processes of secondary succession; we addressed that on the Coiba Island, Panama. We measured tree diameters and determined the land-use histories and structural properties for nine stands. We detected land-use history-legacy gradients ranging from no-use to still-in-use sites (Linear Regressions, R2=0.87 for Above-Ground Biomass and Basal Area, n=7 stands). Three successional pathways derived from a meadow, another from shifting agriculture, another from a >400y-old forest, and four were related to a river and a camp. Our results clarify discussions like convergence-vs-divergence, organismic-vs-individualistic successions, chance-vsdeterminism, and provide land-use history-based suggestions for conservation. [ABSTRACT FROM AUTHOR]

Aim: The climate variability hypothesis proposes that species subjected to wide variation in climatic conditions will evolve wider niches, resulting in larger distributions. We test this hypothesis in tropical plants across a broad elevational gradient; specifically, we use a species‐level approach to evaluate whether elevational range sizes are explained by the levels of thermal variability experienced by species. Location: Central Andes. Time Period: Present day. Taxon: Woody plants. Methods: Combining data from 479 forest plots, we determined the elevational distributions of nearly 2300 species along an elevational gradient (~209–3800 m). For each species, we calculated the maximum annual variation in temperature experienced across its elevational distribution. We used phylogenetic generalized least square models to evaluate the effect of thermal variability on range size. Our models included additional covariates that might affect range size: body size, local abundance, mean temperature and total precipitation. We also considered interactions between thermal variability and mean temperature or precipitation. To account for geometric constraints, we repeated our analyses with a standardized measure of range size, calculated by comparing observed range sizes with values obtained from a null model. Results: Our results supported the main prediction of the climate variability hypothesis. Thermal variability had a strong positive effect on the range size, with species exposed to higher thermal variability having broader elevational distributions. Body size and local abundance also had positive, yet weak effects, on elevational range size. Furthermore, there was a strong positive interaction between thermal variability and mean annual temperature. Main Conclusions: Thermal variability had an overriding importance in driving elevational range sizes of woody plants in the Central Andes. Moreover, the relationship between thermal variability and range size might be even stronger in warmer regions, underlining the potential vulnerability of tropical montane floras to the effects of global warming. [ABSTRACT FROM AUTHOR]

Tropical forests occupy small coral atolls to the vast Amazon basin. They occur across bioregions with different geological and climatic history. Differences in area and bioregional history shape species immigration, extinction and diversification. How this effects local diversity is unclear. The Indonesian archipelago hosts thousands of tree species whose coexistence should depend upon these factors. Using a novel dataset of 215 Indonesian forest plots, across fifteen islands ranging in area from 120 to 785 000 km2, we apply Gaussian mixed effects models to examine the simultaneous effects of environment, earthquake proximity, island area and bioregion upon tree diversity for trees ≥ 10 cm diameter at breast height. We find that tree diversity declines with precipitation seasonality and increases with island area. Accounting for the effects of environment and island area we show that the westernmost bioregion Sunda has greater local diversity than Wallacea, which in turn has greater local diversity than easternmost Sahul. However, when the model includes geological activity (here proximity to major earthquakes), bioregion differences are reduced. Overall, results indicate that multi‐scale, current and historic effects dictate tree diversity. These multi‐scale drivers should not be ignored when studying biodiversity gradients and their impacts upon ecosystem function. [ABSTRACT FROM AUTHOR]

Tropical dry forests are highly threatened at a global scale. Long-term monitoring of remaining stands is needed to assess forest health, efficacy of management practices, and potential impacts of climate change. Using a multi-seasonal Landsat time series, we examined Normalized Difference Vegetation Index (NDVI) patterns in native dry forest, non-native vegetation types, and dry forest restoration sites from 1999 to 2022 in the Hawaiian Islands. We calculated trends in median NDVI and robust coefficient of variation of NDVI for dry and wet seasons, and used Breaks for Additive Seasonal and Trend analysis to detect trend departures. To assess the impact of regional drying trends, NDVI trends were compared to the seasonal long-term precipitation anomaly and cumulative precipitation anomaly. We found that native dry forest was less green than non-native forest, particularly during the dry season, and that median NDVI increased in both native and non-native dry forests over the study period despite negative precipitation anomaly trends. This result differs from coarser-scale studies in Hawaii, but is supported by trends in other dry forest regions. Greening was also observed in restoration study sites, especially larger sites where native species establishment and recruitment has been reported. Non-native grassland NDVI exhibited a strong positive link to precipitation anomalies, suggesting that drier climate scenarios may exacerbate the invasive grass-wildfire cycle that threatens native dry forest. These results demonstrate that Landsat time series may be used to detect seasonal variation in dry forest plots and to support restoration site monitoring in a highly fragmented ecosystem.

International research overflows with studies looking into the causes of construction accidents. Hundreds of studies by postgraduate students in the past 20 years focus on identifying and assessing risks contributing to accidents on Greek construction workplace sites. Many base their work on results from questionnaire surveys that collect the opinions of construction site professionals or on the analysis of data from actual accident records or statistics. Consequently, this study seeks to determine if the data source leads to differing conclusions by using two techniques to synthesize individual results and rank the accident-contributing factors investigated in the original studies. The first utilizes their relative importance index (RII) values, and the second uses their overall ranking index (ORI) to execute meta-analyses. The professional opinion concludes that factors related to operative behavior are the most significant accident-contributing factors. At the same time, actual accident statistics point to site risk factors of the construction process itself as the most important, indicating that expert opinion of Greek professionals should be considered in conjunction with data from actual accident records to provide the focus points for mitigation and assurance of safe construction sites in Greece. [ABSTRACT FROM AUTHOR]

Successfully separating wood and leaves in forest plots is a prerequisite for measuring structural parameters and reconstructing 3D forest models. Terrestrial laser scanning (TLS) can distinguish between the leaves and wood of trees through precise and dense point clouds. However, most existing wood–leaf separation methods face significant accuracy issues, especially in dense forests, due to the complications introduced by canopy shading. In this study, we propose a method to separate the wood and leaves in forest plots using the clustering features of TLS data. The method first filters a point cloud to remove the ground points, and then clusters the point cloud using a region-growing algorithm. Next, the clusters are processed based on their sizes and numbers of points for preliminary separation. Chaos Distance is introduced to characterize the observation that wood points are more orderly while leaf points are more chaotic and disorganized. Lastly, the clusters’ Chaos Distance is used for the final separation. Three representative plots were used to validate this method, achieving an average accuracy of 0.938, a precision of 0.927, a recall of 0.892, and an F1 score of 0.907. The three sample plots were processed in 5.18, 3.75, and 14.52 min, demonstrating high efficiency. Comparing the results with the LeWoS and RF models showed that our method better addresses the accuracy issues of complex canopy structures.

Aim: Andean forests are a global biodiversity hotspot. They harbour many species living within narrow climate ranges and a high functional diversity of trees. It remains still unclear how such hotspots respond to climatic changes over time. We investigated whether Andean forests are changing their functional composition over time along an elevational gradient by assessing changes in species composition, abundance and functional traits. Location: An elevational gradient in Colombia's northern Andes. Time Period: Species composition changes were studied two to four times from 2006 to 2017, and functional composition from 2016 to 2017. Major Taxa Studied: A total of 1104 tropical tree species with in situ traits characterization. Methods: We used seven morphological leaf traits and wood density values to analyse the functional trait dynamic over 10 years along an elevational gradient. By analysing changes in species composition, abundance and trait representation, we inferred the magnitude and direction of changes in functional composition. Then, we assessed if the functional change was related to climate change and demography. Results: With increased minimum temperature and vapour‐pressure deficit, we found a decrease over time in mean values for leaf area and specific leaf area and increases in leaf thickness and leaf dry matter content. Long‐term temperature increases are smaller with increasing elevation, but the magnitude of trait changes is greater than in lowlands. Main Conclusions: The functional composition is changing towards more conservative strategies over time across the elevation gradient, with the strongest changes observed at the highest elevations. This pattern is explained by the change in species turnover within communities due to higher recruitment rates of species with high leaf dry matter content values and low leaf area values. These shifts may be related to communities' responses to higher evapotranspiration demand and thermal stress, mainly at higher elevations. [ABSTRACT FROM AUTHOR]

International research overflows with studies looking into the causes of construction accidents. Hundreds of studies by postgraduate students in the past 20 years focus on identifying and assessing risks contributing to accidents on Greek construction workplace sites. Many base their work on results from questionnaire surveys that collect the opinions of construction site professionals or on the analysis of data from actual accident records or statistics. Consequently, this study seeks to determine if the data source leads to differing conclusions by using two techniques to synthesize individual results and rank the accident-contributing factors investigated in the original studies. The first utilizes their relative importance index (RII) values, and the second uses their overall ranking index (ORI) to execute meta-analyses. The professional opinion concludes that factors related to operative behavior are the most significant accident-contributing factors. At the same time, actual accident statistics point to site risk factors of the construction process itself as the most important, indicating that expert opinion of Greek professionals should be considered in conjunction with data from actual accident records to provide the focus points for mitigation and assurance of safe construction sites in Greece.

Abstract Background The safety and effectiveness of lung segmentectomy in patients with early non-small cell lung cancer (NSCLC) remains controversial. We have therefore reviewed the clinicopathologic characteristics and survival outcomes of patients treated with lobectomy or segmentectomy for early T (> 2 and ≤ 3 cm) N0M0 NSCLC. Methods We obtained data from the Surveillance, Epidemiology, and End Results database for patients who underwent lobectomy or segmentectomy between 2004 and 2015. To reduce bias and imbalances between the treatment groups, propensity score matching analysis was performed. We used Kaplan–Meier curves to estimate overall survival (OS) and lung cancer-specific survival (LCSS). We conducted univariate and multivariate Cox proportional hazards regression analyses to identify independent prognostic factors for OS and cancer-specific survival, and applied the Cox proportional hazards model to create forest plots. Results Before matching, both univariate and multivariate Cox regression analyses revealed that patients who underwent lobectomy exhibited better OS (P 2 and ≤ 3 cm) N0M0 NSCLC undergoing segmentectomy can obtain OS and LCSS similar to those obtained with lobectomy. Further studies are required considering the solid component effects and pathologic tumor types regarding segmentectomies. Additional long-term survival and outcome analyses should be conducted with larger cohorts.

Abstract Amazonian forest plots are used to quantify biodiversity and carbon sequestration, and provide the foundation for much of what is known about tropical ecology. Many plots are assumed to be undisturbed, but recent work suggests that past fire, forest openings, and cultivation created vegetation changes that have persisted for decades to centuries (ecological legacies). The Yasuní Forest Dynamics plot is one of the most biodiverse places on earth, yet its human history remains unknown. Here, we use charcoal and phytolith analysis to investigate the fire and vegetation history of the Yasuní forest plot, and compare results with nearby forest plots in Colombia (Amacayacu) and Peru (Medio Putumayo-Algodón [MPA]) to explore the spatial variability of past disturbances and ecological legacies in northwestern Amazonia. Three 14C dated charcoal fragments provided evidence for a modern (1956 CE) and a past fire event ca. 750 years ago at Yasuní, compared with fire ages of 1000–1600 years ago documented at Amacayacu and MPA. Small-scale disturbances and localized canopy openings also occurred in the Yasuní plot. Phytolith assemblages from Yasuní and Amacayacu showed more variability in past vegetation change than MPA. Lowintensity, non-continuous disturbances occurred at all three plots in the past, and our results highlight the variability of past human activities both in space and time in northwestern Amazonia. Our data also suggest that post-Columbian human disturbances from the Rubber Boom (AD 1850–1920) and subsequent oil exploration have likely left stronger ecological legacies than those left by pre-Columbian peoples in our studied regions [ABSTRACT FROM AUTHOR]

The increasing availability of field data presents an opportunity to understand the fundamental ecological relationships and functions of large trees in tropical forests at regional and global scales. However, it is not always clear what the relationships or patterns of diversity and structure are among sites in different biogeographic regions. We evaluated the relationship of the biomass and diameter of the largest trees with a diversity of species and compared, between the sites, the attributes of structure, diversity, and the influence of the 50 hyperdominant species in each site, aiming at the potential formation of groups by sites with characteristics and patterns of similar diversity within biogeographic regions. The average wood density together with the diversity of genera and families are the most important attributes to discriminate biogeographic regions when considering all forest information. Large trees play a fundamental role in forest ecology and seem to express regional environmental characteristics. The upper canopy of tropical forests remains one of the least studied environments in all terrestrial biomes, and is often referred to as "the last biotic frontier" or a "black box," and large trees are also part of this mysterious frontier. [ABSTRACT FROM AUTHOR]

Background: Oncologists often refer to forest plots to determine which patient subgroups may be more likely to benefit from a therapy tested in a randomized clinical trial (RCT). We sought to empirically determine the information content of subgroup comparisons from forest plots of RCTs. Methods: We assessed all forest plots from RCTs of therapeutic interventions presented orally at the American Society of Clinical Oncology Annual Meetings in 2020 and 2021. Subgroups were considered as showing evidence of treatment effect heterogeneity in forest plots when their confidence intervals (CIs) did not overlap with the vertical line corresponding to the main effect observed in the overall RCT cohort. Subgroups were considered as showing evidence of treatment effect homogeneity in forest plots when their CIs did not meaningfully differ, within 80–125% equivalence range, with the values compatible with the main effect. All other subgroups were considered as inconclusive. Results: A total of 99 forest plots were presented, and only 24.2% contained one or more subgroups suggestive of treatment effect heterogeneity. A total of 81 forest plots provided enough information to evaluate treatment effect heterogeneity and homogeneity. These 81 forest plots represented a total of 1344 individual subgroups, of which 57.2% were inconclusive, 41.1% showed evidence of treatment effect homogeneity, and 1.6% yielded evidence suggestive of treatment effect heterogeneity. Conclusion: The majority of subgroup comparisons were inconclusive in this empirical analysis of forest plots used in oncology RCTs. Different strategies should be considered to improve the estimation and representation of subgroup-specific effects. [ABSTRACT FROM AUTHOR]

Background: The safety and effectiveness of lung segmentectomy in patients with early non-small cell lung cancer (NSCLC) remains controversial. We have therefore reviewed the clinicopathologic characteristics and survival outcomes of patients treated with lobectomy or segmentectomy for early T (> 2 and ≤ 3 cm) N0M0 NSCLC.Methods: We obtained data from the Surveillance, Epidemiology, and End Results database for patients who underwent lobectomy or segmentectomy between 2004 and 2015. To reduce bias and imbalances between the treatment groups, propensity score matching analysis was performed. We used Kaplan-Meier curves to estimate overall survival (OS) and lung cancer-specific survival (LCSS). We conducted univariate and multivariate Cox proportional hazards regression analyses to identify independent prognostic factors for OS and cancer-specific survival, and applied the Cox proportional hazards model to create forest plots.Results: Before matching, both univariate and multivariate Cox regression analyses revealed that patients who underwent lobectomy exhibited better OS (P < 0.001) and LCSS (P = 0.001) than patients who underwent segmentectomy. However, after matching, survival differences between the groups were not significant; OS (P = 0.434) and LCSS (P = 0.593). Regression analyses revealed that age and tumor grade were independent predictors of OS and LCSS (P < 0.05).Conclusions: Patients with stage T (> 2 and ≤ 3 cm) N0M0 NSCLC undergoing segmentectomy can obtain OS and LCSS similar to those obtained with lobectomy. Further studies are required considering the solid component effects and pathologic tumor types regarding segmentectomies. Additional long-term survival and outcome analyses should be conducted with larger cohorts. [ABSTRACT FROM AUTHOR]

Abstract Background The study aims at identifying long-term trends and patterns of current smoking by age, gender, and education in Russia, including the most recent period from 2008 during which tobacco control policies were implemented, and to estimate the impact on mortality of any reductions in prevalence. We present an in-depth analysis based on an unprecedentedly large array of survey data. Methods We examined pooled micro-data on smoking from 17 rounds of the Russian Longitudinal Monitoring Study of 1996–2016, 11 other surveys conducted in Russia in 1975–2017, and two comparator surveys from England and the USA. Standardization by age and education, regression and meta-analysis were used to estimate trends in the prevalence of current smoking by gender, age, and educational patterns. Results From the mid-1970s to the mid-2000s smoking prevalence among men was relatively stable at around 60%, after which time prevalence declined in every age and educational group. Among women, trends in smoking were more heterogeneous. Prevalence more than doubled above the age of 55 years from very low levels (

Copyright of Biotropica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The increasing availability of field data presents an opportunity to understand the fundamental ecological relationships and functions of large trees in tropical forests at regional and global scales. However, it is not always clear what the relationships or patterns of diversity and structure are among sites in different biogeographic regions. We evaluated the relationship of the biomass and diameter of the largest trees with a diversity of species and compared, between the sites, the attributes of structure, diversity, and the influence of the 50 hyperdominant species in each site, aiming at the potential formation of groups by sites with characteristics and patterns of similar diversity within biogeographic regions. The average wood density together with the diversity of genera and families are the most important attributes to discriminate biogeographic regions when considering all forest information. Large trees play a fundamental role in forest ecology and seem to express regional environmental characteristics. The upper canopy of tropical forests remains one of the least studied environments in all terrestrial biomes, and is often referred to as “the last biotic frontier” or a “black box,” and large trees are also part of this mysterious frontier.

The likelihood of a risk factor achieving statistical significance is affected by the overall sample size as well as the distributions of both outcome and predictor variables. Closer attention to confidence intervals and visual displays, in the context of a prespecified determination of effects of interest, contributes to a more comprehensive understanding of the results of a data analysis. [ABSTRACT FROM AUTHOR]

For monitoring and reporting forest carbon stocks and fluxes, many countries in the tropics and subtropics rely on default values of forest aboveground biomass (AGB) from the Intergovernmental Panel on Climate Change (IPCC) guidelines for National Greenhouse Gas (GHG) Inventories. Default IPCC forest AGB values originated from 2006, and are relatively crude estimates of average values per continent and ecological zone. The 2006 default values were based on limited plot data available at the time, methods for their derivation were not fully clear, and no distinction between successional stages was made. As part of the 2019 Refinement to the 2006 IPCC Guidelines for GHG Inventories, we updated the default AGB values for tropical and subtropical forests based on AGB data from >25 000 plots in natural forests and a global AGB map where no plot data were available. We calculated refined AGB default values per continent, ecological zone, and successional stage, and provided a measure of uncertainty. AGB in tropical and subtropical forests varies by an order of magnitude across continents, ecological zones, and successional stage. Our refined default values generally reflect the climatic gradients in the tropics, with more AGB in wetter areas. AGB is generally higher in old-growth than in secondary forests, and higher in older secondary (regrowth >20 years old and degraded/logged forests) than in young secondary forests (⩽20 years old). While refined default values for tropical old-growth forest are largely similar to the previous 2006 default values, the new default values are 4.0–7.7-fold lower for young secondary forests. Thus, the refined values will strongly alter estimated carbon stocks and fluxes, and emphasize the critical importance of old-growth forest conservation. We provide a reproducible approach to facilitate future refinements and encourage targeted efforts to establish permanent plots in areas with data gaps.

Background: Bangladesh has been struggling to reduce the prevalence of childhood undernutrition, which impedes physical and mental capability and accelerates morbidity and mortality. Objectives: The objective of the paper is to examine the changes over time in the association between potential covariates and nutritional status of Bangladeshi children. Methods: The study combined and analyzed data from six waves of Demographic and Health Surveys between 1997 and 2014. Multivariable binary logistic regression models have been fitted to data from individual waves. Overall association has been investigated using forest plots, and meta-regression has been utilized to assess the pace of change in the association over time. Results: Parental education and place of residence showed a consistent association with nutritional status of children. Children from parents with no little education were more likely to be undernourished than those from parents with secondary or higher level of education (odds ratio [OR] in 1997 = 3.34, 95% confidence interval [CI] = 2.65–4.22, OR in 2004 = 1.93, 95% CI = 1.58–2.37). On the other hand, gaps in the association of wealth and childhood nutrition have been widening consistently so that in 2014 children from households from the lowest 40% wealth category were 2.66 times (OR = 2.66, 95% CI = 2.13–3.33) as likely as to be undernourished than those from upper 20%. Conclusions: The findings have policy implications in terms of developing programs directed to mothers with a relatively poor socioeconomic background. A specific example would be providing nutritional education in relation to importance of childhood nutrition or cheaper nutritious food.

Background: The study aims at identifying long-term trends and patterns of current smoking by age, gender, and education in Russia, including the most recent period from 2008 during which tobacco control policies were implemented, and to estimate the impact on mortality of any reductions in prevalence. We present an in-depth analysis based on an unprecedentedly large array of survey data.Methods: We examined pooled micro-data on smoking from 17 rounds of the Russian Longitudinal Monitoring Study of 1996-2016, 11 other surveys conducted in Russia in 1975-2017, and two comparator surveys from England and the USA. Standardization by age and education, regression and meta-analysis were used to estimate trends in the prevalence of current smoking by gender, age, and educational patterns.Results: From the mid-1970s to the mid-2000s smoking prevalence among men was relatively stable at around 60%, after which time prevalence declined in every age and educational group. Among women, trends in smoking were more heterogeneous. Prevalence more than doubled above the age of 55 years from very low levels (< 5%). At younger ages, there were steep increases until the mid-2000s after which prevalence has declined. Trends differed by educational level, with women in the lowest educational category accounting for most of the long-term increase. We estimate that the decline in male smoking may have contributed 6.2% of the observed reduction in cardiovascular deaths among men in the period 2008-16.Conclusions: The implementation of an effective tobacco control strategy in Russia starting in 2008 coincided with a decline in smoking prevalence among men from what had been stable, high levels over many decades regardless of age and education. Among women, the declines have been more uneven, with young women showing recent downturns, while the smoking prevalence in middle age has increased, particularly among those with minimal education. Among men, these positive changes will have made a small contribution to the reduction in mortality seen in Russia since 2005. [ABSTRACT FROM AUTHOR]

Highlights • The widest inter-comparison of regional-to-national AGB maps to date. • Commonalities are observed from the comparison of standardized accuracy assessments. • Retrievals showed RMSE ranging from 10 t ha−1 to 55 t ha−1. • All retrievals present overestimation at low AGB, and underestimation at high AGB. Abstract The amount and spatial distribution of forest aboveground biomass (AGB) were estimated using a range of regionally developed methods using Earth Observation data for Poland, Sweden and regions in Indonesia (Kalimantan), Mexico (Central Mexico and Yucatan peninsula), and South Africa (Eastern provinces) for the year 2010. These regions are representative of numerous forest biomes and biomass levels globally, from South African woodlands and savannas to the humid tropical forest of Kalimantan. AGB retrieval in each region relied on different sources of reference data, including forest inventory plot data and airborne LiDAR observations, and used a range of retrieval algorithms. This is the widest inter-comparison of regional-to-national AGB maps to date in terms of area, forest types, input datasets, and retrieval methods. The accuracy assessment of all regional maps using independent field data or LiDAR AGB maps resulted in an overall root mean square error (RMSE) ranging from 10 t ha−1 to 55 t ha−1 (37% to 67% relative RMSE), and an overall bias ranging from −1 t ha−1 to +5 t ha−1 at pixel level. The regional maps showed better agreement with field data than previously developed and widely used pan-tropical or northern hemisphere datasets. The comparison of accuracy assessments showed commonalities in error structures despite the variety of methods, input data, and forest biomes. All regional retrievals resulted in overestimation (up to 63 t ha−1) in the lower AGB classes, and underestimation (up to 85 t ha−1) in the higher AGB classes. Parametric model-based algorithms present advantages due to their low demand on in situ data compared to non-parametric algorithms, but there is a need for datasets and retrieval methods that can overcome the biases at both ends of the AGB range. The outcomes of this study should be considered when developing algorithms to estimate forest biomass at continental to global scale level. [ABSTRACT FROM AUTHOR]

Fine-scale architectural tree models serve as an effective representation of three-dimensional plant material distributions. They can help to quantify wood volume and biomass, to estimate leaf area distributions on a detailed scale, and can be exploited for physically based modelling approaches. If architectural tree models can be derived for multiple acquisition dates, they permit the detailed investigation of phenological effects. Although promising approaches for the generation of architectural tree/forest models from terrestrial LiDAR data are available, they are often non-trivial and their application to forest plots is often difficult. This is restricting the flexibility of these reconstruction approaches especially for multi-temporal analyses. In this paper, forest models of two Larix decidua forest plots are reconstructed by making use of terrestrial LiDAR data and digital hemispherical photographs (DHP). Recent modelling strategies are enhanced and developed further in order to improve the robustness and usability of the architectural tree model reconstruction process. Raw point cloud data are directly used as input to solve both tree delineation and tree reconstruction in a single processing pipeline. This includes terrain filtering, intensity filtering, and trunk extraction. These steps are followed by a hierarchical and iterative multi-tree branch and twig reconstruction. Based on multi-temporal DHPs, various foliage states are documented. These DHPs and the reconstructed branching architectures are used to flexibly generate and update multi-temporal 3D models of foliage. In order to quantify the modelling performance with respect to various forest characteristics, a test setup based on simulated forest and acquisition geometries is build up. It can be shown, that typical sources of error in the tree reconstruction process are minimized by the proposed approach. It is possible to estimate wood volume distributions, trunk tapering and leaf area distributions with an error of only 10–14%. Except for strongly overlapping tree crowns, the overall accuracy of the single tree delineation in interlinked tree crowns is higher than 80%. Considering these error margins, we apply the modelling strategy to two forest plots and derive architectural models for three dates during the growing season. Using DHPs as reference data, it can be shown, that the estimated gap fraction values derived from the generated models show an error of only 10–15%. [ABSTRACT FROM AUTHOR]

Understanding the processes that determine above-ground biomass ( AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models ( DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity ( NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. [ABSTRACT FROM AUTHOR]

The carbon emissions and removals due to land cover changes between 2001 and 2010 in the Vu Gia Thu Bon River Basin, Central Vietnam, were estimated using Landsat satellite images and 3083 forest inventory plots. The net emissions from above- and belowground vegetation biomass were equal to 1.76 ± 0.12 Tg CO2, about 1.1% of the existing stocks. The vast majority of carbon emissions were due to forest loss, with the conversion of forest to cropland accounting for 67% of net emissions. Forest regrowth had a substantial impact on net carbon changes, removing 22% of emissions from deforestation. Most deforestation occurred in regrowth forest (60%) and plantations (29%), characterized by low carbon stock density. Thus identifying the type of forest where deforestation occurred and using local field data were critical with net emissions being 4 times larger when considering only one forest class with average carbon stock, and 5–7 times higher when using literature default values or global emission maps. Carbon emissions from soil (up to 30 cm) were estimated for the main land change class. Due to the low emission factors from biomass, soils proved a key emission category, accounting for 30% of total land emissions that occurred during the monitoring period. [ABSTRACT FROM AUTHOR]

We combined two existing datasets of vegetation aboveground biomass ( AGB) ( Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha−1 vs. 21 and 28 Mg ha−1 for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets. [ABSTRACT FROM AUTHOR]

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Nano-based products have shown their daunting presence in several sectors. Among them, Zinc Oxide (ZnO) nanoparticles wangled the reputation of providing "next-generation solutions" and are being utilized in plethora of products. Their widespread application has led to increased exposure of these particles, raising concerns regarding toxicological repercussions to the human health and environment. The diversity, complexity, and heterogeneity in the available literature, along with correlation of befitting attributes, makes it challenging to develop one systematic framework to predict this toxicity. The present study aims at developing predictive modelling framework to tap the prospective features responsible for causing cytotoxicity in-vitro on exposure to ZnO nanoparticles. Rigorous approach was used to mine the information from complete body of evidence published to date. The attributes, features and experimental conditions were systematically extracted to unmask the effect of varied features. 1240 data points from 76 publications were obtained, containing 14 qualitative and quantitative attributes, including physiochemical properties of nanoparticles, cell culture and experimental parameters to perform meta-analysis. For the first time, the efforts were made to investigate the degree of significance of attributes accountable for causing cytotoxicity on exposure to ZnO nanoparticles. We show that in-vitro cytotoxicity is closely related with dose concentration of nanoparticles, followed by exposure time, disease state of the cell line and size of these nanoparticles among other attributes. • Meta-analyses of 4446 experiments used 8 decision trees with accuracy up to 94.73%. • Most potent attribute affecting cytotoxicity in-vitro is dose concentration of ZnO. • Model can be replicated for in-vivo and animal based studies for more conclusions. [ABSTRACT FROM AUTHOR]

Amazonian forest plots are used to quantify biodiversity and carbon sequestration, and provide the foundation for much of what is known about tropical ecology. Many plots are assumed to be undisturbed, but recent work suggests that past fire, forest openings, and cultivation created vegetation changes that have persisted for decades to centuries (ecological legacies). The Yasuní Forest Dynamics plot is one of the most biodiverse places on earth, yet its human history remains unknown. Here, we use charcoal and phytolith analysis to investigate the fire and vegetation history of the Yasuní forest plot, and compare results with nearby forest plots in Colombia (Amacayacu) and Peru (Medio Putumayo-Algodón [MPA]) to explore the spatial variability of past disturbances and ecological legacies in northwestern Amazonia. Three 14 C dated charcoal fragments provided evidence for a modern (1956 CE) and a past fire event ca. 750 years ago at Yasuní, compared with fire ages of 1000-1600 years ago documented at Amacayacu and MPA. Small-scale disturbances and localized canopy openings also occurred in the Yasuní plot. Phytolith assemblages from Yasuní and Amacayacu showed more variability in past vegetation change than MPA. Low-intensity, non-continuous disturbances occurred at all three plots in the past, and our results highlight the variability of past human activities both in space and time in northwestern Amazonia. Our data also suggest that post-Columbian human disturbances from the Rubber Boom (AD 1850-1920) and subsequent oil exploration have likely left stronger ecological legacies than those left by pre-Columbian peoples in our studied regions., Competing Interests: The corresponding author confirms on behalf of all authors that there have been no involvements that might raise the question of bias in the work reported or in the conclusions, implications, or opinions stated., (© 2022 The Authors. Biotropica published by Wiley Periodicals LLC on behalf of Association for Tropical Biology and Conservation.)

This study aimed to systematically investigate the effects of different anaesthetics on postoperative physiological reactions compared with placebo. The literature search was conducted using three databases: PubMed, EMBASE, and the Cochrane Library. Studies published from January 1990 to January 2015 were screened. The language was restricted to English. Heterogeneity was analyzed by the Q test and I2 statistic. A fixed-effect model was used for homogenous data and a random-effects model for heterogeneous data. The odds ratio ( OR) and 95% confidence interval ( CI) were calculated to monitor the incidences of overall adverse events, arterial blood pressure, and cardiac abnormalities. Sensitivity analysis was performed to estimate the strength of the meta-analysis, and publication bias was analyzed using Egger's test. A total of 24 articles were included in this meta-analysis. There were 1,810 and 1,806 cases in the anaesthetic group and the placebo group, respectively. The incidence of overall adverse events was significantly lower in the anaesthetic group compared with the placebo group ( OR = 0.57; 95% CI, 0.38-0.84). No publication bias was observed, and no inverse estimates were calculated using sensitivity analysis. There was no significant difference for the incidence of arterial blood pressure ( OR = 4.62; 95% CI, 0.90-23.70) and cardiac abnormalities ( OR = 1.18; 95% CI, 0.53-2.63) between the two groups. Although the incidence of overall adverse events was decreased in the anaesthetic group, it is impossible to determine whether the use of anaesthetics during surgical operation has a protective effect on postoperative physiological reactions. [ABSTRACT FROM AUTHOR]

Systematic reviews (SR) are studies made in order to ask clinical questions based on original articles. Meta-analysis (MTA) is the mathematical analysis of SR. These analyses are divided in two groups, those which evaluate the measured results of quantitative variables (for example, the body mass index --BMI--) and those which evaluate qualitative variables (for example, if a patient is alive or dead, or if he is healing or not). Quantitative variables generally use the mean difference analysis and qualitative variables can be performed using several calculations: odds ratio (OR), relative risk (RR), absolute risk reduction (ARR) and hazard ratio (HR). These analyses are represented through forest plots which allow the evaluation of each individual study, as well as the heterogeneity between studies and the overall effect of the intervention. These analyses are mainly based on Student's t test and Χ². To take appropriate decisions based on the MTA, it is important to understand the characteristics of statistical methods in order to avoid misinterpretations. [ABSTRACT FROM AUTHOR]

Climate change causes shifts in species distributions, or 'migrations'. Despite the centrality of species distributions to biodiversity conservation, the demonstrated large migration of tropical plant species in response to climate change in the past, and the expected sensitivity of species distributions to modern climate change, no study has tested for modern species migrations in tropical plants. Here we conduct a first test of the hypothesis that increasing temperatures are causing tropical trees to migrate to cooler areas. Tropical Andes biodiversity hotspot, south-eastern Peru, South America. We use data from repeated (2003/04-2007/08) censuses of 14 1-ha forest inventory plots spanning an elevational gradient from 950 to 3400 m in Manu National Park in south-eastern Peru, to characterize changes in the elevational distributions of 38 Andean tree genera. We also analyse changes in the genus-level composition of the inventory plots through time. We show that most tropical Andean tree genera shifted their mean distributions upslope over the study period and that the mean rate of migration is approximately 2.5-3.5 vertical metres upslope per year. Consistent with upward migrations we also find increasing abundances of tree genera previously distributed at lower elevations in the majority of study plots. These findings are in accord with the a priori hypothesis of upward shifts in species ranges due to elevated temperatures, and are potentially the first documented evidence of present-day climate-driven migrations in a tropical plant community. The observed mean rate of change is less than predicted from the temperature increases for the region, possibly due to the influence of changes in moisture or non-climatic factors such as substrate, species interactions, lags in tree community response and/or dispersal limitations. Whatever the cause(s), continued slower-than-expected migration of tropical Andean trees would indicate a limited ability to respond to increased temperatures, which may lead to increased extinction risks with further climate change. [ABSTRACT FROM AUTHOR]

Large-fronded tree ferns are critical components of many tropical forests. We investigated frond and whole-plant allometries for Hawaiian keystone species Cibotium glaucum, for prediction and to compare with global scaling relationships. We found that C. glaucum fronds maintain geometric proportionality across a wide range of plant and frond sizes. These relationships result in strong allometries that permit rapid field estimation of frond size from simple linear dimensions. C. glaucum frond allometries complied with intra- and interspecific global trends for leaf area versus mass established for much smaller-leafed species, indicating ‘diminishing returns’ in photosynthetic area per investment in mass for larger fronds. The intraspecific trend was related to declining water content in larger fronds, but not to a significantly larger investment in stipe or rachis relative to lamina. However, C. glaucum complied with the global interspecific trends for greater allocation to support structures in larger leaves. Allometries for frond number and size versus plant height showed that as plants increase in height, frond production and/or retention progressively declines, and the increases of leaf size tend to level off. These frond and whole plant-level relationships indicate the potential for estimating frond area and mass at landscape scale to enrich studies of forest dynamics. [ABSTRACT FROM AUTHOR]

Copyright of Biotropica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)