Drivers and mechanisms of tree mortality in moist tropical forests

Tree mortality rates appear to be increasing in moist tropical forests (MTFs) with significant carbon cycle consequences. Here, we review the state of knowledge regarding MTF tree mortality, create a conceptual framework with testable hypotheses regarding the drivers, mechanisms and interactions that may underlie increasing MTF mortality rates, and identify the next steps for improved understanding and reduced prediction. Increasing mortality rates are associated with rising temperature and vapor pressure deficit, liana abundance, drought, wind events, fire and, possibly, CO2 fertilization-induced increases in stand thinning or acceleration of trees reaching larger, more vulnerable heights. The majority of these mortality drivers may kill trees in part through carbon starvation and hydraulic failure. The relative importance of each driver is unknown. High species diversity may buffer MTFs against large-scale mortality events, but recent and expected trends in mortality drivers give reason for concern regarding increasing mortality within MTFs. Models of tropical tree mortality are advancing the representation of hydraulics, carbon and demography, but require more empirical knowledge regarding the most common drivers and their subsequent mechanisms. We outline critical datasets and model developments required to test hypotheses regarding the underlying causes of increasing MTF mortality rates, and improve prediction of future mortality under climate change

Adiposity indices in the prediction of insulin resistance in prepubertal Colombian children

248-255OBJECTIVE: To compare BMI with abdominal skinfold thickness (ASF), waist circumference and waist-to-height ratio in the prediction of insulin resistance (IR) in prepubertal Colombian children. DESIGN: We calculated age- and sex-specific Z-scores for BMI, ASF, waist circumference, waist-to-height ratio and three other skinfold-thickness sites. Logistic regression with stepwise selection (P = 0·80 for entry and P = 0·05 for retention) was performed to identify predictors of IR and extreme IR, which were determined by age- and sex-specific Z-scores to identify the ≥ 90th and ≥ 95th percentile of homeostasis model assessment (HOMAIR), respectively. We used receiver operating characteristic curves to compare the area under the curve between models. SETTING: Bucaramanga, Colombia. SUBJECTS: Children (n 1261) aged 6-10 years in Tanner stage 1 from a population-based study. RESULTS: A total of 127 children (seventy girls and fifty-seven boys) were classified with IR, including sixty-three children (thirty-three girls and thirty boys) classified with extreme IR. Only ASF and BMI Z-scores were retained as predictors of IR by stepwise selection. Adding ASF Z-score to BMI Z-score improved the area under the curve from 0·794 (95 % CI 0·752, 0·837) to 0·811 (95 % CI 0·770, 0·851; P for contrast = 0·01). In predicting extreme IR, the addition of ASF Z-score to BMI Z-score improved the area under the curve from 0·837 (95 % CI 0·790, 0·884) to 0·864 (95 % CI 0·823, 0·905; P for contrast = 0·01). CONCLUSIONS: ASF Z-score predicted IR independent of BMI Z-score in our population of prepubertal children. ASF and BMI Z-scores together improved IR risk stratification compared with BMI Z-score alone, opening new perspectives in the prediction of cardiometabolic risk in prepubertal children

Prevalence of metabolic syndrome in scholars from Bucaramanga, Colombia : a population-based study

Q11-6Background Obesity and metabolic syndrome are strongly associated with type 2 diabetes mellitus and cardiovascular diseases, thus the increasing trend in their prevalence among children and adolescents from developing countries requires a further understanding of their epidemiology and determinants

Measured and modeled nitrogen balances in lowland rice-pasture rotations in temperate South America

Rotational rice systems, involving pastures, other crops and/or livestock, are common in temperate South America, exemplified by the rice-pasture-livestock system of Uruguay which combines very high rice yields with tight nitrogen (N) balances. The generally good nutrient use efficiency in these systems provides a template for nutrient management in other mixed farming systems, if the underlying processes can be sufficiently well quantified and understood. Here, we studied N balances in rice–non-rice rotations in a long-term experiment in Uruguay, with the aim of parameterizing and testing the DNDC model of N dynamics for such systems for use in future work. The experiment includes three rotations: continuous rice (RI-CONT), rice-soybean (RI-SOY) and rice-pasture (RI-PAST). We considered 9 years of data on N balances (NBAL), defined as all N inputs minus all N outputs; N surplus (NSURP), defined as all N inputs minus only N outputs in food products; and N use efficiency (NUE), defined as the fraction of N inputs removed in food products. We parameterized DNDC against measured yield and input and output data, with missing data on N losses inferred from the N balance and compared with literature values. The model performance was assessed using standard indices of mean error, agreement and efficiency. The model simulated crop yields and rice cumulative N uptake very well, and soil N reasonably well. The values of NBAL were +45 and−20 kg N ha−1 yr−1 in RI-CONT and RI-SOY, respectively, and close to zero in RI-PAST (−6 kg N ha−1 yr−1). Values of NSURP decreased in the order RI-CONT >> RI-SOY > RI-PAST (+115, +25 and +13 kg N ha−1 yr−1, respectively). Values of NUE (84, 54, and 48% for RI-SOY, RI-PAST, and RI-CONT, respectively) decreased as NBAL increased. The sensitivity of DNDC's predictions to the agronomic characteristics of the different crops, rotations and water regimes agreed with expectations. We conclude that the DNDC model as parameterized here is suitable for exploring how to optimize N management in these systems

Rarity of monodominance in hyperdiverse Amazonian forests.

Tropical forests are known for their high diversity. Yet, forest patches do occur in the tropics where a single tree species is dominant. Such "monodominant" forests are known from all of the main tropical regions. For Amazonia, we sampled the occurrence of monodominance in a massive, basin-wide database of forest-inventory plots from the Amazon Tree Diversity Network (ATDN). Utilizing a simple defining metric of at least half of the trees ≥ 10 cm diameter belonging to one species, we found only a few occurrences of monodominance in Amazonia, and the phenomenon was not significantly linked to previously hypothesized life history traits such wood density, seed mass, ectomycorrhizal associations, or Rhizobium nodulation. In our analysis, coppicing (the formation of sprouts at the base of the tree or on roots) was the only trait significantly linked to monodominance. While at specific locales coppicing or ectomycorrhizal associations may confer a considerable advantage to a tree species and lead to its monodominance, very few species have these traits. Mining of the ATDN dataset suggests that monodominance is quite rare in Amazonia, and may be linked primarily to edaphic factors

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

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

Diversity and carbon storage across the tropical forest biome

Tropical forests are global centres of biodiversity and carbon storage. Many tropical countries aspire to protect forest to fulfil biodiversity and climate mitigation policy targets, but the conservation strategies needed to achieve these two functions depend critically on the tropical forest tree diversity-carbon storage relationship. Assessing this relationship is challenging due to the scarcity of inventories where carbon stocks in aboveground biomass and species identifications have been simultaneously and robustly quantified. Here, we compile a unique pan-tropical dataset of 360 plots located in structurally intact old-growth closed-canopy forest, surveyed using standardised methods, allowing a multi-scale evaluation of diversity-carbon relationships in tropical forests. Diversity-carbon relationships among all plots at 1 ha scale across the tropics are absent, and within continents are either weak (Asia) or absent (Amazonia, Africa). A weak positive relationship is detectable within 1 ha plots, indicating that diversity effects in tropical forests may be scale dependent. The absence of clear diversity-carbon relationships at scales relevant to conservation planning means that carbon-centred conservation strategies will inevitably miss many high diversity ecosystems. As tropical forests can have any combination of tree diversity and carbon stocks both require explicit consideration when optimising policies to manage tropical carbon and biodiversity.Additional co-authors: Kofi Affum-Baffoe, Shin-ichiro Aiba, Everton Cristo de Almeida, Edmar Almeida de Oliveira, Patricia Alvarez-Loayza, Esteban Álvarez Dávila, Ana Andrade, Luiz E. O. C. Aragão, Peter Ashton, Gerardo A. Aymard C., Timothy R. Baker, Michael Balinga, Lindsay F. Banin, Christopher Baraloto, Jean-Francois Bastin, Nicholas Berry, Jan Bogaert, Damien Bonal, Frans Bongers, Roel Brienen, José Luís C. Camargo, Carlos Cerón, Victor Chama Moscoso, Eric Chezeaux, Connie J. Clark, Álvaro Cogollo Pacheco, James A. Comiskey, Fernando Cornejo Valverde, Eurídice N. Honorio Coronado, Greta Dargie, Stuart J. Davies, Charles De Canniere, Marie Noel Djuikouo K., Jean-Louis Doucet, Terry L. Erwin, Javier Silva Espejo, Corneille E. N. Ewango, Sophie Fauset, Ted R. Feldpausch, Rafael Herrera, Martin Gilpin, Emanuel Gloor, Jefferson S. Hall, David J. Harris, Terese B. Hart, Kuswata Kartawinata, Lip Khoon Kho, Kanehiro Kitayama, Susan G. W. Laurance, William F. Laurance, Miguel E. Leal, Thomas Lovejoy, Jon C. Lovett, Faustin Mpanya Lukasu, Jean-Remy Makana, Yadvinder Malhi, Leandro Maracahipes, Beatriz S. Marimon, Ben Hur Marimon Junior, Andrew R. Marshall, Paulo S. Morandi, John Tshibamba Mukendi, Jaques Mukinzi, Reuben Nilus, Percy Núñez Vargas, Nadir C. Pallqui Camacho, Guido Pardo, Marielos Peña-Claros, Pascal Pétronelli, Georgia C. Pickavance, Axel Dalberg Poulsen, John R. Poulsen, Richard B. Primack, Hari Priyadi, Carlos A. Quesada, Jan Reitsma, Maxime Réjou-Méchain, Zorayda Restrepo, Ervan Rutishauser, Kamariah Abu Salim, Rafael P. Salomão, Ismayadi Samsoedin, Douglas Sheil, Rodrigo Sierra, Marcos Silveira, J. W. Ferry Slik, Lisa Steel, Hermann Taedoumg, Sylvester Tan, John W. Terborgh, Sean C. Thomas, Marisol Toledo, Peter M. Umunay, Luis Valenzuela Gamarra, Ima Célia Guimarães Vieira, Vincent A. Vos, Ophelia Wang, Simon Willcock & Lise Zemagh