The Q10 coefficient is the ratio of reaction rates at two temperatures 10°C apart, and has
been widely applied to quantify the temperature sensitivity of organic matter decomposition. However, biogeochemists and ecologists have long recognized that a constant Q10 coefficient does not describe the temperature sensitivity of organic matter decomposition accurately. To examine the consequences of the constant Q10 assumption, we built a biogeochemical reaction model to simulate anaerobic organic matter decomposition in peatlands in the Upper Peninsula of Michigan, USA, and compared the simulation results to the predictions with Q10 coefficients. By accounting for the reactions of extracellular enzymes, mesophilic fermenting and methanogenic microbes, and their temperature responses, the biogeochemical reaction model reproduces the observations of previous laboratory incubation experiments, including the temporal variations in the concentrations of dissolved organic carbon, acetate, dihydrogen, carbon dioxide, and methane, and confirms that fermentation limits the progress of anaerobic organic matter decomposition. The modeling results illustrate the oversimplification inherent in the constant Q10 assumption and how the assumption undermines the kinetic prediction of anaerobic organic matter decomposition. In particular, the model predicts that between 5°C and 30°C, the decomposition rate increases almost linearly with increasing temperature, which stands in sharp contrast to the exponential relationship given by the Q10 coefficient. As a result, the constant Q10 approach tends to underestimate the rates of organic matter decomposition within the temperature ranges where Q10 values are determined, and overestimate the rates outside the temperature ranges. The results also show how biogeochemical reaction modeling, combined with laboratory experiments, can help uncover the temperature sensitivity of organic matter decomposition arising from underlying catalytic mechanisms.
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Low temperature sensitivity of picophytoplankton P:B ratios and growth rates across a natural 10°C temperature gradient in the oligotrophic Indian Ocean
We investigated temperature sensitivities of picophytoplankton growth along a natural 10°C (18-28°C) temperature gradient in the eastern Indian Ocean characterized by deep mixing and consistently low dissolved nitrogen. Population biomass (B), cell carbon and chlorophyll were measured by flow cytometry. Instantaneous growth (µ) and production (P) were calculated from dilution incubations at four light levels. Contrary to most empirical and theoretical predictions, Prochlorococcus, the biomass dominant, showed insignificant temperature sensitivity, with nominal Q10 values of 1.06 and 1.18 for P:B and µ, respectively, and activation energies (Ea) of 0.05 and 0.12 eV. Q10 and Ea values for Synechococcus (1.36-1.42 and 0.23-0.27 eV) were also below prediction, and picoeukaryotes showed high variability, including negative rates suggesting lytic cycles, at high temperature. We emphasize the importance of using adapted communities in natural environmental gradients to test climate predictions and hypothesize that mortality defenses are a significant selection criterion in balanced oligotrophic systems.
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- Award ID(s):
- 1851558
- NSF-PAR ID:
- 10334678
- Date Published:
- Journal Name:
- Limnology and oceanography letters
- Volume:
- 7
- ISSN:
- 2378-2242
- Page Range / eLocation ID:
- 112–121
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Aim Tropical elevation gradients are natural laboratories to assess how changing climate can influence tropical forests. However, there is a need for theory and integrated data collection to scale from traits to ecosystems. We assess predictions of a novel trait‐based scaling theory, including whether observed shifts in forest traits across a broad tropical temperature gradient are consistent with local phenotypic optima and adaptive compensation for temperature.
Location An elevation gradient spanning 3,300 m and consisting of thousands of tropical tree trait measures taken from 16 1‐ha tropical forest plots in southern Perú, where gross and net primary productivity (GPP and NPP) were measured.
Time period April to November 2013.
Major taxa studied Plants; tropical trees.
Methods We developed theory to scale from traits to communities and ecosystems and tested several predictions. We assessed the covariation between climate, traits, biomass and GPP and NPP. We measured multiple traits linked to variation in tree growth and assessed their frequency distributions within and across the elevation gradient. We paired these trait measures across individuals within 16 forests with simultaneous measures of ecosystem net and gross primary productivity.
Results Consistent with theory, variation in forest NPP and GPP primarily scaled with forest biomass, but the secondary effect of temperature on productivity was much less than expected. This weak temperature dependence appears to reflect directional shifts in several mean community traits that underlie tree growth with decreases in site temperature.
Main conclusions The observed shift in traits of trees that dominate in more cold environments is consistent with an ‘adaptive/acclimatory’ compensation for the kinetic effects of temperature on leaf photosynthesis and tree growth. Forest trait distributions across the gradient showed overly peaked and skewed distributions, consistent with the importance of local filtering of optimal growth traits and recent shifts in species composition and dominance attributable to warming from climate change. Trait‐based scaling theory provides a basis to predict how shifts in climate have and will influence the trait composition and ecosystem functioning of tropical forests.
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Abstract Understanding the observed temperature dependence of decomposition (i.e., its apparent activation energy) requires separation of direct effects of temperature on consumer metabolism (i.e., the inherent activation energy) from those driven by indirect seasonal patterns in phenology and biomass, and by longer‐term, climate‐driven shifts in acclimation, adaptation, and community assembly. Such parsing is important because studies that relate temperature to decomposition usually involve multi‐season data and/or spatial proxies for long‐term shifts, and so incorporate these indirect factors. The various effects of such factors can obscure the inherent temperature dependence of detrital processing. Separating the inherent temperature dependence of decomposition from other drivers is important for accurate prediction of the contribution of detritus‐sourced greenhouse gases to climate warming and requires novel approaches to data collection and analysis. Here, we present breakdown rates of red maple litter incubated in coarse‐ and fine‐mesh litterbags (the latter excluding macroinvertebrates) for serial approximately one‐month increments over one year in nine streams along a natural temperature gradient (mean annual: 12.8°–16.4°C) from north Georgia to central Alabama, USA. We analyzed these data using distance‐based redundancy analysis and generalized additive mixed models to parse the dependence of decomposition rates on temperature, seasonality, and shredding macroinvertebrate biomass. Microbial decomposition in fine‐mesh bags was significantly influenced by both temperature and seasonality. Accounting for seasonality corrected the temperature dependence of decomposition rate from 0.25 to 0.08 eV. Shredder assemblage structure in coarse‐mesh bags was related to temperature across both sites and seasons, shifting from “cold” stonefly‐dominated communities to “warm” communities dominated by snails or crayfish. Shredder biomass was not a significant predictor of either coarse‐mesh or macroinvertebrate‐mediated (i.e., coarse‐ minus fine‐mesh) breakdown rates, which were also jointly influenced by temperature and seasonality. Unlike fine‐mesh bags, however, temperature dependence of litter breakdown did not differ between models with and without seasonality for either coarse‐mesh (0.36 eV) or macroinvertebrate‐mediated (0.13 eV) rates. We conclude that indirect (non‐thermal) seasonal and site‐level effects play a variable and potentially strong role in shaping the apparent temperature dependence of detrital breakdown. Such effects should be incorporated into studies designed to estimate inherent temperature dependence of slow ecological processes.
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Abstract Because seawater temperature is correlated with viscosity, temperature changes may impact small zooplankton through a mechanical pathway, separately from any thermally-induced effects on metabolism. We evaluated both viscous and thermal effects on copepod feeding in experiments where viscosity was manipulated separately from temperature using a non-toxic polymer. Two copepod species, Acartia tonsa and Parvocalanus crassirostris, feeding on two monoalgal diets (a diatom and a dinoflagellate) were compared. At constant temperature, increase in viscosity nearly always reduced feeding; at constant viscosity, changes in temperature had no effect on feeding. The effects of viscosity and temperature were more pronounced for the diatom than the flagellate prey. Overall, reductions in zooplankton feeding at cold temperatures can be explained primarily by the mechanical effect of viscosity. Q10 values for copepod feeding (1.0–7.9), calculated from the present data and from the literature, were generally higher and more variable than Q10 values from the literature for copepod respiration (1.5–3.1) indicating that, at cold temperatures, feeding is more dramatically suppressed than metabolism. We conclude that (i) high viscosity may inhibit copepod feeding, and (ii) this viscous effect on feeding (rather than a thermal effect on metabolism) may influence the cold-temperature bounds of zooplankton populations.
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Abstract. Urbanization and deforestation have important impacts on atmosphericparticulate matter (PM) over Amazonia. This study presents observations andanalysis of PM1 concentration, composition, and opticalproperties in central Amazonia during the dry season, focusing on theanthropogenic impacts. The primary study site was located 70 km downwind ofManaus, a city of over 2 million people in Brazil, as part of theGoAmazon2014/5 experiment. A high-resolution time-of-flight aerosol massspectrometer (AMS) provided data on PM1 composition, and aethalometermeasurements were used to derive the absorption coefficient babs,BrC ofbrown carbon (BrC) at 370 nm. Non-refractory PM1 mass concentrationsaveraged 12.2 µg m−3 at the primary study site, dominated byorganics (83 %), followed by sulfate (11 %). A decrease inbabs,BrC was observed as the mass concentration of nitrogen-containingorganic compounds decreased and the organic PM1 O:C ratio increased,suggesting atmospheric bleaching of the BrC components. The organic PM1was separated into six different classes by positive-matrix factorization(PMF), and the mass absorption efficiency Eabs associated with eachfactor was estimated through multivariate linear regression ofbabs,BrC on the factor loadings. The largest Eabs values wereassociated with urban (2.04±0.14 m2 g−1) and biomass-burning(0.82±0.04 to 1.50±0.07 m2 g−1) sources. Together, these sources contributed at least 80 % ofbabs,BrC while accounting for 30 % to 40 % of the organic PM1 massconcentration. In addition, a comparison of organic PM1 compositionbetween wet and dry seasons revealed that only part of the 9-foldincrease in mass concentration between the seasons can be attributed tobiomass burning. Biomass-burning factor loadings increased by 30-fold,elevating its relative contribution to organic PM1 from about 10 % inthe wet season to 30 % in the dry season. However, most of the PM1mass (>60 %) in both seasons was accounted for by biogenicsecondary organic sources, which in turn showed an 8-fold seasonalincrease in factor loadings. A combination of decreased wet deposition andincreased emissions and oxidant concentrations, as well as a positivefeedback on larger mass concentrations are thought to play a role in theobserved increases. Furthermore, fuzzy c-means clustering identified threeclusters, namely “baseline”, “event”, and “urban” to representdifferent pollution influences during the dry season. The baseline cluster,representing the dry season background, was associated with a mean massconcentration of 9±3 µg m−3. This concentration increasedon average by 3 µg m−3 for both the urban and the event clusters.The event cluster, representing an increased influence of biomass burningand long-range transport of African volcanic emissions, was characterized byremarkably high sulfate concentrations. The urban cluster, representing theinfluence of Manaus emissions on top of the baseline, was characterized byan organic PM1 composition that differed from the other two clusters.The differences discussed suggest a shift in oxidation pathways as well asan accelerated oxidation cycle due to urban emissions, in agreement withfindings for the wet season.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/doi.org/10.1002/lol2.10224.
