Carlos A. Sierra

Relationships among net primary productivity, nutrients and climate in tropical rain forest: a pan-tropical analysis

Tropical rain forests play a dominant role in global biosphere-atmosphere CO(2) exchange. Although climate and nutrient availability regulate net primary production (NPP) and decomposition in all terrestrial ecosystems, the nature and extent of such controls in tropical forests remain poorly resolved. We conducted a meta-analysis of carbon-nutrient-climate relationships in 113 sites across the tropical forest biome. Our analyses showed that mean annual temperature was the strongest predictor of aboveground NPP (ANPP) across all tropical forests, but this relationship was driven by distinct temperature differences between upland and lowland forests. Within lowland forests (< 1000 m), a regression tree analysis revealed that foliar and soil-based measurements of phosphorus (P) were the only variables that explained a significant proportion of the variation in ANPP, although the relationships were weak. However, foliar P, foliar nitrogen (N), litter decomposition rate (k), soil N and soil respiration were all directly related with total surface (0-10 cm) soil P concentrations. Our analysis provides some evidence that P availability regulates NPP and other ecosystem processes in lowland tropical forests, but more importantly, underscores the need for a series of large-scale nutrient manipulations - especially in lowland forests - to elucidate the most important nutrient interactions and controls.

Plant diversity increases soil microbial activity and soil carbon storage

Plant diversity strongly influences ecosystem functions and services, such as soil carbon storage. However, the mechanisms underlying the positive plant diversity effects on soil carbon storage are poorly understood. We explored this relationship using long-term data from a grassland biodiversity experiment (The Jena Experiment) and radiocarbon ((14)C) modelling. Here we show that higher plant diversity increases rhizosphere carbon inputs into the microbial community resulting in both increased microbial activity and carbon storage. Increases in soil carbon were related to the enhanced accumulation of recently fixed carbon in high-diversity plots, while plant diversity had less pronounced effects on the decomposition rate of existing carbon. The present study shows that elevated carbon storage at high plant diversity is a direct function of the soil microbial community, indicating that the increase in carbon storage is mainly limited by the integration of new carbon into soil and less by the decomposition of existing soil carbon.

Toward more realistic projections of soil carbon dynamics by Earth system models

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.

Temperature sensitivity of organic matter decomposition in the Arrhenius equation: some theoretical considerations

Previous theoretical analyses based on Arrhenius kinetics and thermodynamics have shown that the temperature sensitivity of low-quality substrate is higher than that of high-quality substrate. Because soils store large amounts of low-quality carbon, understanding its response to increasing temperatures will help to predict the response of atmospheric CO2 to climate change. However, empirical studies do not provide conclusive evidence to corroborate this theoretical argument. Although there are various possible reasons for this disagreement, the theory behind this argument has not been scrutinized carefully. Based on a simple mathematical analysis of the Arrhenius equation it is shown here that low-quality substrates are less temperature sensitive when analyzed in absolute rather than in relative terms, a result that may seem counterintuitive to previous theory. However, this is a paradox intrinsic to the Arrhenius equation and it is often ignored within the ‘quality-temperature’ debate. In fact, different measures commonly used to analyze the temperature sensitivity of different substrates can provide apparently different and contradictory results even though they are based on the same basic principles. Distinguishing between absolute and relative measures of sensitivity is essential for understanding the sensitivity of respiration to environmental change. An analysis of the available empirical evidence on this topic shows that most studies actually agree with the Arrhenius and thermodynamics theory, with less disagreement than previously thought. To address some of the issues identified here, a formal theoretical framework is proposed to study the sensitivity of respiration rates with respect to changes in multiple drivers of decomposition.

Sensitivity of decomposition rates of soil organic matter with respect to simultaneous changes in temperature and moisture

© 2015. The Authors. The sensitivity of soil organic matter decomposition to global environmental change is a topic of prominent relevance for the global carbon cycle. Decomposition depends on multiple factors that are being altered simultaneously as a result of global environmental change; therefore, it is important to study the sensitivity of the rates of soil organic matter decomposition with respect to multiple and interacting drivers. In this manuscript, we present an analysis of the potential response of decomposition rates to simultaneous changes in temperature and moisture. To address this problem, we first present a theoretical framework to study the sensitivity of soil organic matter decomposition when multiple driving factors change simultaneously. We then apply this framework to models and data at different levels of abstraction: (1) to a mechanistic model that addresses the limitation of enzyme activity by simultaneous effects of temperature and soil water content, the latter controlling substrate supply and oxygen concentration for microbial activity; (2) to different mathematical functions used to represent temperature and moisture effects on decomposition in biogeochemical models. To contrast model predictions at these two levels of organization, we compiled different data sets of observed responses in field and laboratory studies. Then we applied our conceptual framework to: (3) observations of heterotrophic respiration at the ecosystem level; (4) laboratory experiments looking at the response of heterotrophic respiration to independent changes in moisture and temperature; and (5) ecosystem-level experiments manipulating soil temperature and water content simultaneously.

Interannual variation of carbon fluxes from three contrasting evergreen forests: the role of forest dynamics and climate

Interannual variation of carbon fluxes can be attributed to a number of biotic and abiotic controls that operate at different spatial and temporal scales. Type and frequency of disturbance, forest dynamics, and climate regimes are important sources of variability. Assessing the variability of carbon fluxes from these specific sources can enhance the interpretation of past and current observations. Being able to separate the variability caused by forest dynamics from that induced by climate will also give us the ability to determine if the current observed carbon fluxes are within an expected range or whether the ecosystem is undergoing unexpected change. Sources of interannual variation in ecosystem carbon fluxes from three evergreen ecosystems, a tropical, a temperate coniferous, and a boreal forest, were explored using the simulation model STANDCARB. We identified key processes that introduced variation in annual fluxes, but their relative importance differed among the ecosystems studied. In the tropical site, intrinsic forest dynamics contributed approximately 30% of the total variation in annual carbon fluxes. In the temperate and boreal sites, where many forest processes occur over longer temporal scales than those at the tropical site, climate controlled more of the variation among annual fluxes. These results suggest that climate-related variability affects the rates of carbon exchange differently among sites. Simulations in which temperature, precipitation, and radiation varied from year to year (based on historical records of climate variation) had less net carbon stores than simulations in which these variables were held constant (based on historical records of monthly average climate), a result caused by the functional relationship between temperature and respiration. This suggests that, under a more variable temperature regime, large respiratory pulses may become more frequent and high enough to cause a reduction in ecosystem carbon stores. Our results also show that the variation of annual carbon fluxes poses an important challenge in our ability to determine whether an ecosystem is a source, a sink, or is neutral in regard to CO2 at longer timescales. In simulations where climate change negatively affected ecosystem carbon stores, there was a 20% chance of committing Type II error, even with 20 years of sequential data.

Decomposition of heterogeneous organic matter and its long-term stabilization in soils

Soil organic matter is a complex mixture of material with heterogeneous biological, physical, and chemical properties. Decomposition models represent this heterogeneity either as a set of discrete pools with different residence times or as a continuum of qualities. It is unclear though, whether these two different approaches yield comparable predictions of organic matter dynamics. Here, we compare predictions from these two different approaches and propose an intermediate approach to study organic matter decomposition based on concepts from continuous models implemented numerically. We found that the disagreement between discrete and continuous approaches can be considerable depending on the degree of nonlinearity of the model and simulation time. The two approaches can diverge substantially for predicting long-term processes in soils. Based on our alternative approach, which is a modification of the continuous quality theory, we explored the temporal patterns that emerge by treating substrate heterogenei...

The muddle of ages, turnover, transit, and residence times in the carbon cycle

Comparisons among ecosystem models or ecosystem dynamics along environmental gradients commonly rely on metrics that integrate different processes into a useful diagnostic. Terms such as age, turnover, residence, and transit times are often used for this purpose; however, these terms are variably defined in the literature and in many cases, calculations ignore assumptions implicit in their formulas. The aim of this opinion piece was i) to make evident these discrepancies and the incorrect use of formulas, ii) highlight recent results that simplify calculations and may help to avoid confusion, and iii) propose the adoption of simple and less ambiguous terms.

A general mathematical framework for representing soil organic matter dynamics

We propose here a general mathematical framework to represent soil organic matter dynamics. This framework is expressed in the language of dynamical systems and generalizes previous modeling approaches. It is based on a set of six basic principles about the decomposition of soil organic matter: (1) mass balance, (2) substrate dependence of decomposition, (3) heterogeneity of the speed of decay, (4) internal transformations of organic matter, (5) environmental variability effects, and (6) substrate interactions. We show how the majority of models previously proposed are special cases of this general model. This approach provides tools to classify models according to the main principles or concepts they include. It also helps to identify a priori the general behavior of different models or groups of models. Another important characteristic of the proposed mathematical representation is the possibility to develop particular models at any level of detail. This characteristic is described as a modeling hierarchy, in which a general model of a high degree of abstraction can accommodate specific realizations of model structure for specific modeling objectives. This framework also allows us to study general properties of groups of models such as their qualitative behavior, timescale of application, and their dynamic stability. For instance, we find conditions under which models are asymptotically stable, i.e., converge to a stable steady state in the long term, but may approach this state with or without oscillations. We also expand the concept of dynamic stability for models that include time dependencies and do not converge to a fixed steady state, but rather to a region of stability in the state-space. As an example of the application of the concept of dynamic stability, we show how this framework helps to explain the acclimation of soil respiration fluxes in soil-warming experiments.

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.