Trophic dynamics of methylmercury and trace elements in a remote Amazonian Lake.

peer reviewedInformation on pollutant trophodynamics can be crucial for public health, as contaminated food consumption may lead to deleterious effects. This study was performed in Puruzinho Lake, a remote body of water in the Brazilian Amazon from which a riparian human population obtains an important part of its animal protein intake. Samples from 92 individuals, comprising 13 species and four trophic guilds (iliophagous, planktivorous, omnivorous, and piscivorous fish) were analysed for the determination of trace elements (Fe, Cr, Mn, Ni, Zn, Ca, Sr, Cd, Sn, Tl and Pb) and methylmercury concentrations. Samples from the same individuals had already been analysed for stable isotope (SI) measurements (δ13C and δ15N) in a previous investigation and the SI data have been statistically treated with those generated in this study for the evaluation of trophic dynamics of contaminants. Methylmercury was the only analyte that biomagnified, presenting TMF values of 4.65 and 4.55 for total and resident ichthyofauna, respectively. Trace elements presented either trophic dilution or independence from the trophic position, constituting a behaviour that was coherent with that found in the scientific literature. The similarity between Ni behaviour through the trophic web to that of essential elements contributes to the discussion on the essentiality of this metal to fish. Considering the Non-cancer Risk Assessment, the calculated Target Hazard Quotient (THQ) values were higher than 1.0 for all analysed individuals for methylmercury, as well as for only one individual for nickel. No other analyte rendered THQ values higher than 1.0.14. Life below wate

Isoprene emission structures tropical tree biogeography and community assembly responses to climate.

The prediction of vegetation responses to climate requires a knowledge of how climate-sensitive plant traits mediate not only the responses of individual plants, but also shifts in the species and functional compositions of whole communities. The emission of isoprene gas – a trait shared by one-third of tree species – is known to protect leaf biochemistry under climatic stress. Here, we test the hypothesis that isoprene emission shapes tree species compositions in tropical forests by enhancing the tolerance of emitting trees to heat and drought. Using forest inventory data, we estimated the proportional abundance of isoprene-emitting trees (pIE) at 103 lowland tropical sites. We also quantified the temporal composition shifts in three tropical forests – two natural and one artificial – subjected to either anomalous warming or drought. Across the landscape, pIE increased with site mean annual temperature, but decreased with dry season length. Through time, pIE strongly increased under high temperatures, and moderately increased following drought. Our analysis shows that isoprene emission is a key plant trait determining species responses to climate. For species adapted to seasonal dry periods, isoprene emission may tradeoff with alternative strategies, such as leaf deciduousness. Community selection for isoprene-emitting species is a potential mechanism for enhanced forest resilience to climatic change.Financial support for this study was provided to: T.C.T. and S.R.S. by grants NSF-PIRE #OISE-0730305, USDOE #3002937712, NASA #NNX17AF65G and the University of AZ Agnes Nelms Haury Program in Environment and Social Justice; to M.N.S. and S.R.S. by NASA-ESSF #NNX14AK95H; to C.V. by ERCStG-2014-639706-CONSTRAINTS; to I.S. by Grant Agency of the Czech Republic #16-26369S; and to P.M. by NERC # NE/ N006852/1 and ARC #DP170104091

Height-diameter allometry of tropical forest trees

Copyright © 2011 European Geosciences Union. This is the published version available at http://www.biogeosciences.net/8/1081/2011/bg-8-1081-2011.html doi:10.5194/bg-8-1081-2011Tropical tree height-diameter (H:D) relationships may vary by forest type and region making large-scale estimates of above-ground biomass subject to bias if they ignore these differences in stem allometry. We have therefore developed a new global tropical forest database consisting of 39 955 concurrent H and D measurements encompassing 283 sites in 22 tropical countries. Utilising this database, our objectives were: 1. to determine if H:D relationships differ by geographic region and forest type (wet to dry forests, including zones of tension where forest and savanna overlap). 2. to ascertain if the H:D relationship is modulated by climate and/or forest structural characteristics (e.g. stand-level basal area, A). 3. to develop H:D allometric equations and evaluate biases to reduce error in future local-to-global estimates of tropical forest biomass. Annual precipitation coefficient of variation (PV), dry season length (SD), and mean annual air temperature (TA) emerged as key drivers of variation in H:D relationships at the pantropical and region scales. Vegetation structure also played a role with trees in forests of a high A being, on average, taller at any given D. After the effects of environment and forest structure are taken into account, two main regional groups can be identified. Forests in Asia, Africa and the Guyana Shield all have, on average, similar H:D relationships, but with trees in the forests of much of the Amazon Basin and tropical Australia typically being shorter at any given D than their counterparts elsewhere. The region-environment-structure model with the lowest Akaike's information criterion and lowest deviation estimated stand-level H across all plots to within amedian −2.7 to 0.9% of the true value. Some of the plot-to-plot variability in H:D relationships not accounted for by this model could be attributed to variations in soil physical conditions. Other things being equal, trees tend to be more slender in the absence of soil physical constraints, especially at smaller D. Pantropical and continental-level models provided less robust estimates of H, especially when the roles of climate and stand structure in modulating H:D allometry were not simultaneously taken into account

Evolutionary Heritage Influences Amazon Tree Ecology

Lineages tend to retain ecological characteristics of their ancestors through time. However, for some traits, selection during evolutionary history may have also played a role in determining trait values. To address the relative importance of these processes requires large-scale quantification of traits and evolutionary relationships among species. The Amazonian tree flora comprises a high diversity of angiosperm lineages and species with widely differing life-history characteristics, providing an excellent system to investigate the combined influences of evolutionary heritage and selection in determining trait variation. We used trait data related to the major axes of life-history variation among tropical trees (e.g. growth and mortality rates) from 577 inventory plots in closed-canopy forest, mapped onto a phylogenetic hypothesis spanning more than 300 genera including all major angiosperm clades to test for evolutionary constraints on traits. We found significant phylogenetic signal (PS) for all traits, consistent with evolutionarily related genera having more similar characteristics than expected by chance. Although there is also evidence for repeated evolution of pioneer and shade tolerant life-history strategies within independent lineages, the existence of significant PS allows clearer predictions of the links between evolutionary diversity, ecosystem function and the response of tropical forests to global change

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Long-term thermal sensitivity of Earth’s tropical forests

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost