Increasing dominance of large lianas in Amazonian forests

Ecological orthodoxy suggests that old-growth forests should be close to dynamic equilibrium, but this view has been challenged by recent findings that neotropical forests are accumulating carbon and biomass, possibly in response to the increasing atmospheric concentrations of carbon dioxide. However, it is unclear whether the recent increase in tree biomass has been accompanied by a shift in community composition. Such changes could reduce or enhance the carbon storage potential of old-growth forests in the long term. Here we show that non-fragmented Amazon forests are experiencing a concerted increase in the density, basal area and mean size of woody climbing plants (lianas). Over the last two decades of the twentieth century the dominance of large lianas relative to trees has increased by 1.7–4.6% a year. Lianas enhance tree mortality and suppress tree growth, so their rapid increase implies that the tropical terrestrial carbon sink may shut down sooner than current models suggest. Predictions of future tropical carbon fluxes will need to account for the changing composition and dynamics of supposedly undisturbed forests

A study of resiliency among Chinese health care workers: Capacity to cope with workplace stress

This paper reports a study of resiliency to cope with workplace stress among Chinese health care workers. We adopted a qualitative-quantitative-biomarker approach to conduct interviews, focus group discussions, and a two-wave longitudinal survey. Wave 1 survey was conducted among health care workers in Hong Kong and Mainland China (N = 773). Amongst them, 287 took part in Wave 2 survey. A confirmatory factor analysis consistently supported a 9-item scale. A sub-sample's (N = 33) resiliency was positively related to salivary IgA levels (an immune marker). Results from hierarchical regressions demonstrated that resiliency measured in Wave 1 was positively related to job satisfaction, work-life balance, and quality of life; and negatively related to physical/psychological symptoms and injuries at work in Wave 2. © 2009 Elsevier Inc. All rights reserved.postprin

The importance of crown dimensions to improve tropical tree biomass estimates

Tropical forests play a vital role in the global carbon cycle, but the amount of carbon they contain and its spatial distribution remain uncertain. Recent studies suggest that once tree height is accounted for in biomass calculations, in addition to diameter and wood density, carbon stock estimates are reduced in many areas. However, it is possible that larger crown sizes might offset the reduction in biomass estimates in some forests where tree heights are lower because even comparatively short trees develop large, well-lit crowns in or above the forest canopy. While current allometric models and theory focus on diameter, wood density, and height, the influence of crown size and structure has not been well studied.To test the extent to which accounting for crown parameters can improve biomass estimates, we harvested and weighed 51 trees (11–169 cm diameter) in southwestern Amazonia where no direct biomass measurements have been made. The trees in our study had nearly half of total above ground biomass in the branches (44% ± 2% [mean ± SE]), demonstrating the importance of accounting for tree crowns. Consistent with our predictions, key pantropical equations that include height, but do not account for crown dimensions, underestimated the sum total biomass of all 51 trees by 11% to 14%, primarily due to substantial underestimates of many of the largest trees. In our models, including crown radius greatly improves performance and reduces error, especially for the largest trees. In addition, over the full data set, crown radius explained more variation in above ground biomass (10.5%) than height (6.0%). Crown form is also important: trees with a monopodial architectural type are estimated to have 21–44% less mass than trees with other growth patterns. Our analysis suggests that accounting for crown allometry would substantially improve the accuracy of tropical estimates of tree biomass and its distribution in primary and degraded forests

Variations in soil chemical and physical properties explain basin-wide Amazon forest soil carbon concentrations

We investigate the edaphic, mineralogical and climatic controls of soil organic carbon (SOC) concentration utilising data from 147 primary forest soils (0–30 cm depth) sampled in eight different countries across the Amazon Basin. Sampled across 14 different World Reference Base soil groups, our data suggest that stabilisation mechanism varies with pedogenetic level. Specifically, although SOC concentrations in Ferralsols and Acrisols were best explained by simple variations in clay content – this presumably being due to their relatively uniform kaolinitic mineralogy – this was not the case for less weathered soils such as Alisols, Cambisols and Plinthosols for which interactions between Al species, soil pH and litter quality are argued to be much more important. Although for more strongly weathered soils the majority of SOC is located within the aggregate fraction, for the less weathered soils most of the SOC is located within the silt and clay fractions. It thus seems that for highly weathered soils SOC storage is mostly influenced by surface area variations arising from clay content, with physical protection inside aggregates rendering an additional level of protection against decomposition. On the other hand, most of the SOC in less weathered soils is associated with the precipitation of aluminium–carbon complexes within the fine soil fraction, with this mechanism enhanced by the presence of high levels of aromatic, carboxyl-rich organic matter compounds. Also examined as part of this study were a relatively small number of arenic soils (viz. Arenosols and Podzols) for which there was a small but significant influence of clay and silt content variations on SOM storage, with fractionation studies showing that particulate organic matter may account for up to 0.60 of arenic soil SOC. In contrast to what were in all cases strong influences of soil and/or litter quality properties, after accounting for these effects neither wood productivity, above-ground biomass nor precipitation/temperature variations were found to exert any significant influence on SOC stocks. These results have important implications for our understanding of how Amazon forest soils are likely to respond to ongoing and future climate changes

The impact of long dry periods on the aboveground biomass in a tropical forest: 20 years of monitoring

Background Long-term studies of community and population dynamics indicate that abrupt disturbances often catalyse changes in vegetation and carbon stocks. These disturbances include the opening of clearings, rainfall seasonality, and drought, as well as fire and direct human disturbance. Such events may be super-imposed on longer-term trends in disturbance, such as those associated with climate change (heating, drying), as well as resources. Intact neotropical forests have recently experienced increased drought frequency and fire occurrence, on top of pervasive increases in atmospheric CO2 concentrations, but we lack long-term records of responses to such changes especially in the critical transitional areas at the interface of forest and savanna biomes. Here, we present results from 20 years monitoring a valley forest (moist tropical forest outlier) in central Brazil. The forest has experienced multiple drought events and includes plots which have and which have not experienced fire. We focus on how forest structure (stem density and aboveground biomass carbon) and dynamics (stem and biomass mortality and recruitment) have responded to these disturbance regimes. Results Overall, the biomass carbon stock increased due to the growth of the trees already present in the forest, without any increase in the overall number of tree stems. Over time, both recruitment and especially mortality of trees tended to increase, and periods of prolonged drought in particular resulted in increased mortality rates of larger trees. This increased mortality was in turn responsible for a decline in aboveground carbon toward the end of the monitoring period. Conclusion Prolonged droughts influence the mortality of large trees, leading to a decline in aboveground carbon stocks. Here, and in other neotropical forests, recent droughts are capable of shutting down and reversing biomass carbon sinks. These new results add to evidence that anthropogenic climate changes are already adversely impacting tropical forests

Necromass in forests of Madre de Dios, Peru: A comparison between terra firme and lowland forests

This is the final version of the article. Available from Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Biológicas via the DOI in this record.Stocks of dead wood or necromass represent an important portion of biomass and nutrients in tropical forests. The objectives of this study were: 1) to evaluate and compare the necromass of “terra firme” and lowlands forests, (2) to study the relationship between necromass, above-ground biomass and wood density, and (3) to estimate the necromass of the department of Madre de Dios, Peru. Stocks of necromass and above-ground biomass were estimated at three different locations using permanent plots and line intercept transects. The average volume of necromass for the three sites was 72.9 m3 ha-1 with an average weight varying between 24.8 and 30.7 Mg ha-1, depending on the estimations of dead wood density used for the calculations. Terra firme forests had significantly higher stocks of necromass than lowland forests. The amount of necromass was 11% of the total above-ground biomass in Madre de Dios forests. The total stock of carbon stored in dead wood for the entire department of Madre de Dios was estimated to be approximately 100 mega tonnes of carbon. This is ten times more than the annual fossil fuel emissions of Peru between 2000 and 2008. The substantial stocks of necromass emphasize the importance of these types of field studies, considering that this component of tropical forest carbon cannot be detected using other methods such as satellite remote sensing

Size and frequency of natural forest disturbances and the Amazon forest carbon balance

types: Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.Copyright © 2014 Macmillan Publishers Limited. All rights reserved.This is an open-access articleForest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel combination of forest inventory, airborne lidar and satellite remote sensing data. We find that small-scale mortality events are responsible for aboveground biomass losses of ~1.7 Pg C y(-1) over the entire Amazon region. We also find that intermediate-scale disturbances account for losses of ~0.2 Pg C y(-1), and that the largest-scale disturbances as a result of blow-downs only account for losses of ~0.004 Pg C y(-1). Simulation of growth and mortality indicates that even when all carbon losses from intermediate and large-scale disturbances are considered, these are outweighed by the net biomass accumulation by tree growth, supporting the inference of an Amazon carbon sink.NASA Earth System Science Fellowship (NESSF

Regional Mapping and Spatial Distribution Analysis of Canopy Palms in an Amazon Forest Using Deep Learning and VHR Images

Mapping plant species at the regional scale to provide information for ecologists and forest managers is a challenge for the remote sensing community. Here, we use a deep learning algorithm called U-net and very high-resolution multispectral images (0.5 m) from GeoEye satellite to identify, segment and map canopy palms over ∼3000 km2 of Amazonian forest. The map was used to analyse the spatial distribution of canopy palm trees and its relation to human disturbance and edaphic conditions. The overall accuracy of the map was 95.5% and the F1-score was 0.7. Canopy palm trees covered 6.4% of the forest canopy and were distributed in more than two million patches that can represent one or more individuals. The density of canopy palms is affected by human disturbance. The post-disturbance density in secondary forests seems to be related to the type of disturbance, being higher in abandoned pasture areas and lower in forests that have been cut once and abandoned. Additionally, analysis of palm trees’ distribution shows that their abundance is controlled naturally by local soil water content, avoiding both flooded and waterlogged areas near rivers and dry areas on the top of the hills. They show two preferential habitats, in the low elevation above the large rivers, and in the slope directly below the hill tops. Overall, their distribution over the region indicates a relatively pristine landscape, albeit within a forest that is critically endangered because of its location between two deforestation fronts and because of illegal cutting. New tree species distribution data, such as the map of all adult canopy palms produced in this work, are urgently needed to support Amazon species inventory and to understand their distribution and diversity

Mapping Atlantic rainforest degradation and regeneration history with indicator species using convolutional network

The Atlantic rainforest of Brazil is one of the global terrestrial hotspots of biodiversity. Despite having undergone large scale deforestation, forest cover has shown signs of increases in the last decades. Here, to understand the degradation and regeneration history of Atlantic rainforest remnants near São Paulo, we combine a unique dataset of very high resolution images from Worldview-2 and Worldview-3 (0.5 and 0.3m spatial resolution, respectively), georeferenced aerial photographs from 1962 and use a deep learning method called U-net to map (i) the forest cover and changes and (ii) two pioneer tree species, Cecropia hololeuca and Tibouchina pulchra. For Tibouchina pulchra, all the individuals were mapped in February, when the trees undergo mass-flowering with purple and pink blossoms. Additionally, elevation data at 30m spatial resolution from NASA Shuttle Radar Topography Mission (SRTM) and annual mean climate variables (Terraclimate datasets at ∼ 4km of spatial resolution) were used to analyse the forest and species distributions. We found that natural forests are currently more frequently found on south-facing slopes, likely because of geomorphology and past land use, and that Tibouchina is restricted to the wetter part of the region (southern part), which annually receives at least 1600 mm of precipitation. Tibouchina pulchra was found to clearly indicate forest regeneration as almost all individuals were found within or adjacent to forests regrown after 1962. By contrast, Cecropia hololeuca was found to indicate older disturbed forests, with all individuals almost exclusively found in forest fragments already present in 1962. At the regional scale, using the dominance maps of both species, we show that at least 4.3% of the current region’s natural forests have regrown after 1962 (Tibouchina dominated, ∼ 4757 ha) and that ∼ 9% of the old natural forests have experienced significant disturbance (Cecropia dominated)

Assessment of Bias in Pan-Tropical Biomass Predictions

Above-ground biomass (AGB) is an essential descriptor of forests, of use in ecological and climate-related research. At tree- and stand-scale, destructive but direct measurements of AGB are replaced with predictions from allometric models characterizing the correlational relationship between AGB, and predictor variables including stem diameter, tree height and wood density. These models are constructed from harvested calibration data, usually via linear regression. Here, we assess systematic error in out-of-sample predictions of AGB introduced during measurement, compilation and modeling of in-sample calibration data. Various conventional bivariate and multivariate models are constructed from open access data of tropical forests. Metadata analysis, fit diagnostics and cross-validation results suggest several model misspecifications: chiefly, unaccounted for inconsistent measurement error in predictor variables between in- and out-of-sample data. Simulations demonstrate conservative inconsistencies can introduce significant bias into tree- and stand-scale AGB predictions. When tree height and wood density are included as predictors, models should be modified to correct for bias. Finally, we explore a fundamental assumption of conventional allometry, that model parameters are independent of tree size. That is, the same model can provide predictions of consistent trueness irrespective of size-class. Most observations in current calibration datasets are from smaller trees, meaning the existence of a size dependency would bias predictions for larger trees. We determine that detecting the absence or presence of a size dependency is currently prevented by model misspecifications and calibration data imbalances. We call for the collection of additional harvest data, specifically under-represented larger trees