Individual-Based Modeling of Amazon Forests Suggests That Climate Controls Productivity While Traits Control Demography

Climate, species composition, and soils are thought to control carbon cycling and forest structure in Amazonian forests. Here, we add a demographics scheme (tree recruitment, growth, and mortality) to a recently developed non-demographic model—the Trait-based Forest Simulator (TFS)—to explore the roles of climate and plant traits in controlling forest productivity and structure. We compared two sites with differing climates (seasonal vs. aseasonal precipitation) and plant traits. Through an initial validation simulation, we assessed whether the model converges on observed forest properties (productivity, demographic and structural variables) using datasets of functional traits, structure, and climate to model the carbon cycle at the two sites. In a second set of simulations, we tested the relative importance of climate and plant traits for forest properties within the TFS framework using the climate from the two sites with hypothetical trait distributions representing two axes of functional variation (“fast” vs. “slow” leaf traits, and high vs. low wood density). The adapted model with demographics reproduced observed variation in gross (GPP) and net (NPP) primary production, and respiration. However, NPP and respiration at the level of plant organs (leaf, stem, and root) were poorly simulated. Mortality and recruitment rates were underestimated. The equilibrium forest structure differed from observations of stem numbers suggesting either that the forests are not currently at equilibrium or that mechanisms are missing from the model. Findings from the second set of simulations demonstrated that differences in productivity were driven by climate, rather than plant traits. Contrary to expectation, varying leaf traits had no influence on GPP. Drivers of simulated forest structure were complex, with a key role for wood density mediated by its link to tree mortality. Modeled mortality and recruitment rates were linked to plant traits alone, drought-related mortality was not accounted for. In future, model development should focus on improving allocation, mortality, organ respiration, simulation of understory trees and adding hydraulic traits. This type of model that incorporates diverse tree strategies, detailed forest structure and realistic physiology is necessary if we are to be able to simulate tropical forest responses to global change scenarios

The presence of peat and variation in tree species composition are under different hydrological controls in Amazonian wetland forests

This research was funded by the Gordon and Betty Moore Foundation, through grant #5349 ‘Monitoring protected areas in Peru to increase forest resilience to climate change’, and NERC standard grant ‘Carbon Storage in Amazonian Peatlands: Distribution and Dynamics’(NE/R000751/1).The peat-forming wetland forests of Amazonia are characterised by high below-carbon stocks and supply fruit, fibres and timber to local communities. Predicting the future of these ecosystem services requires understanding how hydrological conditions are related to tree species composition and the presence, or absence, of peat. Here, we use continuous measurements of water table depth over 2.5 years and manual measurements of pore-water pH and electrical conductivity to understand the ecohydrological controls of these variables across the large peatland complex in northern Peruvian Amazonia. Measurements were taken in permanent forest plots in four palm swamps, four seasonally flooded forests and four peatland pole forests. All trees ≥10 cm diameter were also measured and identified in the plots to assess floristic composition. Peat occurs in eight of these twelve sites; three seasonally flooded forests and one palm swamp are not associated with peat. Variation in tree species composition among forest types was linked to high flood levels (maximum flooding height) and pH: seasonally flooded forests experience high flood levels (up to 3.66 m from the ground surface) and have high pH values (6?7), palm swamps have intermediate flood levels (up to 1.34 m) and peatland pole forests experience shallow flooding (up to 0.28 m) and have low pH (4). In contrast, the presence of peat was linked to variation in maximum water table depth (ie the depth to which the water table drops below the ground surface). Surface peat is found in all forest types where maximum water table depth does not fall >0.55 m below the ground surface at any time. Peat formation and variation in tree species composition therefore have different ecohydrological controls. Predicted increases in the frequency and strength of flooding events may alter patterns of tree species composition, whereas increases in drought severity and declines in minimum river levels may pose a greater risk to the belowground carbon stores of these peatland ecosystems.Publisher PDFPeer reviewe

Thinner bark increases sensitivity of wetter Amazonian tropical forests to fire

Understory fires represent an accelerating threat to Amazonian tropical forests and can, during drought, affect larger areas than deforestation itself. These fires kill trees at rates varying from < 10 to c. 90% depending on fire intensity, forest disturbance history and tree functional traits. Here, we examine variation in bark thickness across the Amazon. Bark can protect trees from fires, but it is often assumed to be consistently thin across tropical forests. Here, we show that investment in bark varies, with thicker bark in dry forests and thinner in wetter forests. We also show that thinner bark translated into higher fire‐driven tree mortality in wetter forests, with between 0.67 and 5.86 gigatonnes CO2 lost in Amazon understory fires between 2001 and 2010. Trait‐enabled global vegetation models that explicitly include variation in bark thickness are likely to improve the predictions of fire effects on carbon cycling in tropical forests

Interventions associated with brown adipose tissue activation and the impact on energy expenditure and weight loss: A systematic review

BackgroundBrown adipose tissue (BAT) plays a role in modulating energy expenditure. People with obesity have been shown to have reduced activation of BAT. Agents such as β-agonists, capsinoids, thyroid hormone, sildenafil, caffeine, or cold exposure may lead to activation of BAT in humans, potentially modulating metabolism to promote weight loss.MethodsWe systematically searched electronic databases for clinical trials testing the effect of these agents and cold exposure on energy expenditure/thermogenesis and the extent to which they may impact weight loss in adults.ResultsA total of 695 studies from PubMed, Web of Science, and Medline electronic databases were identified. After the removal of duplicates and further evaluation, 47 clinical trials were analyzed. We observed significant heterogeneity in the duration of interventions and the metrics utilized to estimate thermogenesis/energy expenditure. Changes observed in energy expenditure do not correlate with major weight changes with different interventions commonly known to stimulate thermogenesis. Even though cold exposure appears to consistently activate BAT and induce thermogenesis, studies are small, and it appears to be an unlikely sustainable therapy to combat obesity. Most studies were small and potential risks associated with known side effects of some agents such as β-agonists (tachycardia), sibutramine (hypertension, tachycardia), thyroid hormone (arrhythmias) cannot be fully evaluated from these small trials.ConclusionThough the impact of BAT activation and associated increases in energy expenditure on clinically meaningful weight loss is a topic of great interest, further data is needed to determine long-term feasibility and efficacy

From Sea to Shining Sea and the Great Plains to Patagonia: A Review on Current Knowledge of Diabetes Mellitus in Hispanics/Latinos in the US and Latin America

The past two decades have witnessed many advances in the prevention, treatment, and control of diabetes mellitus (DM) and its complications. Increased screening has led to a greater recognition of type 2 diabetes mellitus (type 2 DM) and prediabetes; however, Hispanics/Latinos, the largest minority group in the US, have not fully benefited from these advances. The Hispanic/Latino population is highly diverse in ancestries, birth places, cultures, languages, and socioeconomic backgrounds, and it populates most of the Western Hemisphere. In the US, the prevalence of DM varies among Hispanic/Latino heritage groups, being higher among Mexicans, Puerto Ricans, and Dominicans, and lower among South Americans. The risk and prevalence of diabetes among Hispanics/Latinos are significantly higher than in non-Hispanic Whites, and nearly 40% of Hispanics/Latinos with diabetes have not been formally diagnosed. Despite these striking facts, the representation of Hispanics/Latinos in pharmacological and non-pharmacological clinical trials has been suboptimal, while the prevalence of diabetes in these populations continues to rise. This review will focus on the epidemiology, etiology and prevention of type 2 DM in populations of Latin American origin. We will set the stage by defining the terms Hispanic, Latino, and Latin American, explaining the challenges identifying Hispanics/Latinos in the scientific literature and databases, describing the epidemiology of diabetes—including type 2 DM and gestational diabetes mellitus (GDM)—and cardiovascular risk factors in Hispanics/Latinos in the US and Latin America, and discussing trends, and commonalities and differences across studies and populations, including methodology to ascertain diabetes. We will discuss studies on mechanisms of disease, and research on prevention of type 2 DM in Hispanics/Latinos, including women with GDM, youth and adults; and finalize with a discussion on lessons learned and opportunities to enhance research, and, consequently, clinical care oriented toward preventing type 2 DM in Hispanics/Latinos in the US and Latin America

Tropical Peatland Hydrology Simulated With a Global Land Surface Model

Tropical peatlands are among the most carbon-dense ecosystems on Earth, and their water storage dynamics strongly control these carbon stocks. The hydrological functioning of tropical peatlands differs from that of northern peatlands, which has not yet been accounted for in global land surface models (LSMs). Here, we integrated tropical peat-specific hydrology modules into a global LSM for the first time, by utilizing the peatland-specific model structure adaptation (PEATCLSM) of the NASA Catchment Land Surface Model (CLSM). We developed literature-based parameter sets for natural (PEATCLSM(Trop,Nat)) and drained (PEATCLSM(Trop,Drain)) tropical peatlands. Simulations with PEATCLSM(Trop,Nat) were compared against those with the default CLSM version and the northern version of PEATCLSM (PEATCLSM(North,Nat)) with tropical vegetation input. All simulations were forced with global meteorological reanalysis input data for the major tropical peatland regions in Central and South America, the Congo Basin, and Southeast Asia. The evaluation against a unique and extensive data set of in situ water level and eddy covariance-derived evapotranspiration showed an overall improvement in bias and correlation compared to the default CLSM version. Over Southeast Asia, an additional simulation with PEATCLSM(Trop,Drain) was run to address the large fraction of drained tropical peatlands in this region. PEATCLSM(Trop,Drain) outperformed CLSM, PEATCLSM(North,Nat), and PEATCLSM(Trop,Nat) over drained sites. Despite the overall improvements of PEATCLSM(Trop,Nat) over CLSM, there are strong differences in performance between the three study regions. We attribute these performance differences to regional differences in accuracy of meteorological forcing data, and differences in peatland hydrologic response that are not yet captured by our model.Peer reviewe

Leaf-level photosynthetic capacity in lowland Amazonian and high elevation, Andean tropical moist forests of Peru

We examined whether variations in photosynthetic capacity are linked to variations in theenvironment and/or associated leaf traits for tropical moist forests (TMFs) in the Andes/west-ern Amazon regions of Peru. We compared photosynthetic capacity (maximal rate of carboxylation of Rubisco (Vcmax),and the maximum rate of electron transport (Jmax)), leaf mass, nitrogen (N) and phosphorus(P) per unit leaf area (Ma,Naand Pa, respectively), and chlorophyll from 210 species at 18field sites along a 3300-m elevation gradient. Western blots were used to quantify the abun-dance of the CO₂-fixing enzyme Rubisco. Area- and N-based rates of photosynthetic capacity at 25°C were higher in upland than low-land TMFs, underpinned by greater investment of N in photosynthesis in high-elevation trees. Soil [P] and leaf Pa were key explanatory factors for models of area-based Vcmax and Jmax but did not account for variations in photosynthetic N-use efficiency. At any given Na and Pa, the fraction of N allocated to photosynthesis was higher in upland than lowland species. For a smallsubset of lowland TMF trees examined, a substantial fraction of Rubisco was inactive. These results highlight the importance of soil- and leaf-P in defining the photosyntheticcapacity of TMFs, with variations in N allocation and Rubisco activation state further influenc-ing photosynthetic rates and N-use efficiency of these critically important forests

Seasonal trends of Amazonian rainforest phenology, net primary productivity, and carbon allocation.:Seasonal trends of Amazonian forests.

The seasonality of solar irradiance and precipitation may regulate seasonal variations in tropical forests carbon cycling. Controversy remains over their importance as drivers of seasonal dynamics of net primary productivity in tropical forests. We use ground data from nine lowland Amazonian forest plots collected over 3 years to quantify the monthly primary productivity (NPP) of leaves, reproductive material, woody material, and fine roots over an annual cycle. We distinguish between forests that do not experience substantial seasonal moisture stress (“humid sites”) and forests that experience a stronger dry season (“dry sites”). We find that forests from both precipitation regimes maximize leaf NPP over the drier season, with a peak in production in August at both humid (mean 0.39 ± 0.03 Mg C ha−1 month−1 in July, n = 4) and dry sites (mean 0.49 ± 0.03 Mg C ha−1 month−1 in September, n = 8). We identify two distinct seasonal carbon allocation patterns (the allocation of NPP to a specific organ such as wood leaves or fine roots divided by total NPP). The forests monitored in the present study show evidence of either (i) constant allocation to roots and a seasonal trade-off between leaf and woody material or (ii) constant allocation to wood and a seasonal trade-off between roots and leaves. Finally, we find strong evidence of synchronized flowering at the end of the dry season in both precipitation regimes. Flower production reaches a maximum of 0.047 ± 0.013 and 0.031 ± 0.004 Mg C ha−1 month−1 in November, in humid and dry sites, respectively. Fruitfall production was staggered throughout the year, probably reflecting the high variation in varying times to development and loss of fruit among species

Fine root dynamics across pantropical rainforest ecosystems

Fine roots constitute a significant component of the net primary productivity (NPP) of forest ecosystems but are much less studied than aboveground NPP. Comparisons across sites and regions are also hampered by inconsistent methodologies, especially in tropical areas. Here, we present a novel dataset of fine root biomass, productivity, residence time, and allocation in tropical old-growth rainforest sites worldwide, measured using consistent methods, and examine how these variables are related to consistently determined soil and climatic characteristics. Our pantropical dataset spans intensive monitoring plots in lowland (wet, semi-deciduous, and deciduous) and montane tropical forests in South America, Africa, and Southeast Asia (n = 47). Large spatial variation in fine root dynamics was observed across montane and lowland forest types. In lowland forests, we found a strong positive linear relationship between fine root productivity and sand content, this relationship was even stronger when we considered the fractional allocation of total NPP to fine roots, demonstrating that understanding allocation adds explanatory power to understanding fine root productivity and total NPP. Fine root residence time was a function of multiple factors: soil sand content, soil pH, and maximum water deficit, with longest residence times in acidic, sandy, and water-stressed soils. In tropical montane forests, on the other hand, a different set of relationships prevailed, highlighting the very different nature of montane and lowland forest biomes. Root productivity was a strong positive linear function of mean annual temperature, root residence time was a strong positive function of soil nitrogen content in montane forests, and lastly decreasing soil P content increased allocation of productivity to fine roots. In contrast to the lowlands, environmental conditions were a better predictor for fine root productivity than for fractional allocation of total NPP to fine roots, suggesting that root productivity is a particularly strong driver of NPP allocation in tropical mountain regions.WHH was funded by Peruvian FONDECYT/CONCYTEC (grant contract number 213-2015-FONDECYT). The GEM network was supported by a European Research Council Advanced Investigator Grant to YM (GEM-TRAITS: 321131) under the European Union's Seventh Framework Programme (FP7/2007-2013). The field data collection was funded NERC Grants NE/D014174/1 and NE/J022616/1 for in Peru, BALI (NE/K016369/1) for work in Malaysia, the Royal Society-Leverhulme Africa Capacity Building Programme for work in Ghana and Gabon and ESPA-ECOLIMITS (NE/1014705/1) in Ghana and Ethiopia. Plot inventories in South America were supported by funding from the US National Science Foundation Long-Term Research in Environmental Biology program (LTREB; DEB 1754647) and the Gordon and Betty Moore Foundation Andes-Amazon Program. GEM data in Gabon were collected under authorization to YM and supported by the Gabon National Parks Agency. Y.M. is supported by the Jackson Foundation. We would like to acknowledge the GEM team across the tropical regions and countries of Bolivia, Brazil, Ghana, Gabon, Ethiopia, Malaysia, and Peru