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Abstract Plants and mycorrhizal fungi form mutualistic relationships that affect how resources flow between organisms and within ecosystems. Common mycorrhizal networks (CMNs) could facilitate preferential transfer of carbon and limiting nutrients, but this remains difficult to predict. Do CMNs favour fungal resource acquisition at the expense of plant resource demands (a fungi‐centric view), or are they passive channels through which plants regulate resource fluxes (a plant‐centric view)?We used stable isotope tracers (¹³CO₂and¹⁵NH₃), plant traits, and mycorrhizal DNA to quantify above‐ and below‐ground carbon and nitrogen transfer between 18 plant species along a 520‐km latitudinal gradient in the Pacific Northwest, USA.Plant functional type and tissue stoichiometry were the most important predictors of interspecific resource transfer. Of ‘donor’ plants, 98% were¹³C‐enriched, but we detected transfer in only 2% of ‘receiver’ plants. However, all donors were¹⁵N‐enriched and we detected transfer in 81% of receivers. Nitrogen was preferentially transferred to annuals (0.26 ± 0.50 mg N per g leaf mass) compared with perennials (0.13 ± 0.30 mg N per g leaf mass). This corresponded with tissue stoichiometry differences.SynthesisOur findings suggest that plants and fungi that are located closer together in space and with stronger demand for resources over time are more likely to receive larger amounts of those limiting resources. Read the freePlain Language Summaryfor this article on the Journal blog. 

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. 

Abstract TheQ₁₀coefficient 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 constantQ₁₀coefficient does not describe the temperature sensitivity of organic matter decomposition accurately. To examine the consequences of the constantQ₁₀assumption, 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 withQ₁₀coefficients. 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 constantQ₁₀assumption 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 theQ₁₀coefficient. As a result, the constantQ₁₀approach tends to underestimate the rates of organic matter decomposition within the temperature ranges whereQ₁₀values 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. 

Abstract Understanding the chemical composition of our planet's crust was one of the biggest questions of the 20th century. More than 100 years later, we are still far from understanding the global patterns in the bioavailability and spatial coupling of elements in topsoils worldwide, despite their importance for the productivity and functioning of terrestrial ecosystems. Here, we measured the bioavailability and coupling of thirteen macro‐ and micronutrients and phytotoxic elements in topsoils (3–8 cm) from a range of terrestrial ecosystems across all continents (∼10,000 observations) and in response to global change manipulations (∼5,000 observations). For this, we incubated between 1 and 4 pairs of anionic and cationic exchange membranes per site for a mean period of 53 days. The most bioavailable elements (Ca, Mg, and K) were also amongst the most abundant in the crust. Patterns of bioavailability were biome‐dependent and controlled by soil properties such as pH, organic matter content and texture, plant cover, and climate. However, global change simulations resulted in important alterations in the bioavailability of elements. Elements were highly coupled, and coupling was predictable by the atomic properties of elements, particularly mass, mass to charge ratio, and second ionization energy. Deviations from the predictable coupling‐atomic mass relationship were attributed to global change and agriculture. Our work illustrates the tight links between the bioavailability and coupling of topsoil elements and environmental context, human activities, and atomic properties of elements, thus deeply enhancing our integrated understanding of the biogeochemical connections that underlie the productivity and functioning of terrestrial ecosystems in a changing world. 

Abstract Wetlands cover a small portion of the world, but have disproportionate influence on global carbon (C) sequestration, carbon dioxide and methane emissions, and aquatic C fluxes. However, the underlying biogeochemical processes that affect wetland C pools and fluxes are complex and dynamic, making measurements of wetland C challenging. Over decades of research, many observational, experimental, and analytical approaches have been developed to understand and quantify pools and fluxes of wetland C. Sampling approaches range in their representation of wetland C from short to long timeframes and local to landscape spatial scales. This review summarizes common and cutting-edge methodological approaches for quantifying wetland C pools and fluxes. We firstdefineeach of the major C pools and fluxes and providerationalefor their importance to wetland C dynamics. For each approach, we clarifywhatcomponent of wetland C is measured and its spatial and temporal representativeness and constraints. We describe practical considerations for each approach, such aswhereandwhenan approach is typically used,whocan conduct the measurements (expertise, training requirements), andhowapproaches are conducted, including considerations on equipment complexity and costs. Finally, we reviewkey covariatesandancillary measurementsthat enhance the interpretation of findings and facilitate model development. The protocols that we describe to measure soil, water, vegetation, and gases are also relevant for related disciplines such as ecology. Improved quality and consistency of data collection and reporting across studies will help reduce global uncertainties and develop management strategies to use wetlands as nature-based climate solutions.