David Medvigy

Mechanistic scaling of ecosystem function and dynamics in space and time: Ecosystem Demography model version 2

[1] Insights into how terrestrial ecosystems affect the Earth’s response to changes in climate and rising atmospheric CO2 levels rely heavily on the predictions of terrestrial biosphere models (TBMs). These models contain detailed mechanistic representations of biological processes affecting terrestrial ecosystems; however, their ability to simultaneously predict field-based measurements of terrestrial vegetation dynamics and carbon fluxes has remained largely untested. In this study, we address this issue by developing a constrained implementation of a new structured TBM, the Ecosystem Demography model version 2 (ED2), which explicitly tracks the dynamics of fine-scale ecosystem structure and function. Carbon and water flux measurements from an eddy-flux tower are used in conjunction with forest inventory measurements of tree growth and mortality at Harvard Forest (42.5N, 72.1W) to estimate a number of important but weakly constrained model parameters. Evaluation against a decade of tower flux and forest dynamics measurements shows that the constrained ED2 model yields greatly improved predictions of annual net ecosystem productivity, carbon partitioning, and growth and mortality dynamics of both hardwood and conifer trees. The generality of the model formulation is then evaluated by comparing the model’s predictions against measurements from two other eddy-flux towers and forest inventories of the northeastern United States and Quebec. Despite the markedly different composition throughout this region, the optimized model realistically predicts observed patterns of carbon fluxes and tree growth. These results demonstrate how TBMs parameterized with field-based measurements can provide quantitative insight into the underlying biological processes governing ecosystem composition, structure, and function at larger scales.

Responses of terrestrial ecosystems and carbon budgets to current and future environmental variability

We assess the significance of high-frequency variability of environmental parameters (sunlight, precipitation, temperature) for the structure and function of terrestrial ecosystems under current and future climate. We examine the influence of hourly, daily, and monthly variance using the Ecosystem Demography model version 2 in conjunction with the long-term record of carbon fluxes measured at Harvard Forest. We find that fluctuations of sunlight and precipitation are strongly and nonlinearly coupled to ecosystem function, with effects that accumulate through annual and decadal timescales. Increasing variability in sunlight and precipitation leads to lower rates of carbon sequestration and favors broad-leaved deciduous trees over conifers. Temperature variability has only minor impacts by comparison. We also find that projected changes in sunlight and precipitation variability have important implications for carbon storage and ecosystem structure and composition. Based on Intergovernmental Panel on Climate Change model estimates for changes in high-frequency meteorological variability over the next 100 years, we expect that terrestrial ecosystems will be affected by changes in variability almost as much as by changes in mean climate. We conclude that terrestrial ecosystems are highly sensitive to high-frequency meteorological variability, and that accurate knowledge of the statistics of this variability is essential for realistic predictions of ecosystem structure and functioning.

Predicting ecosystem dynamics at regional scales: an evaluation of a terrestrial biosphere model for the forests of northeastern North America.

Terrestrial biosphere models are important tools for diagnosing both the current state of the terrestrial carbon cycle and forecasting terrestrial ecosystem responses to global change. While there are a number of ongoing assessments of the short-term predictive capabilities of terrestrial biosphere models using flux-tower measurements, to date there have been relatively few assessments of their ability to predict longer term, decadal-scale biomass dynamics. Here, we present the results of a regional-scale evaluation of the Ecosystem Demography version 2 (ED2)-structured terrestrial biosphere model, evaluating the models predictions against forest inventory measurements for the northeast USA and Quebec from 1985 to 1995. Simulations were conducted using a default parametrization, which used parameter values from the literature, and a constrained model parametrization, which had been developed by constraining the models predictions against 2 years of measurements from a single site, Harvard Forest (42.5° N, 72.1° W). The analysis shows that the constrained model parametrization offered marked improvements over the default model formulation, capturing large-scale variation in patterns of biomass dynamics despite marked differences in climate forcing, land-use history and species-composition across the region. These results imply that data-constrained parametrizations of structured biosphere models such as ED2 can be successfully used for regional-scale ecosystem prediction and forecasting. We also assess the models ability to capture sub-grid scale heterogeneity in the dynamics of biomass growth and mortality of different sizes and types of trees, and then discuss the implications of these analyses for further reducing the remaining biases in the models predictions.

Terrestrial hydrological controls on land surface phenology of African savannas and woodlands

This paper presents a continental-scale phenological analysis of African savannas and woodlands. We apply an array of synergistic vegetation and hydrological data records from satellite remote sensing and model simulations to explore the influence of rainy season timing and duration on regional land surface phenology and ecosystem structure. We find that (i) the rainy season onset precedes and is an effective predictor of the growing season onset in African grasslands. (ii) African woodlands generally have early green-up before rainy season onset and have a variable delayed senescence period after the rainy season, with this delay correlated nonlinearly with tree fraction. These woodland responses suggest their complex water use mechanisms (either from potential groundwater use by relatively deep roots or stem-water reserve) to maintain dry season activity. (iii) We empirically find that the rainy season length has strong nonlinear impacts on tree fractional cover in the annual rainfall range from 600 to 1800 mm/yr, which may lend some support to the previous modeling study that given the same amount of total rainfall to the tree fraction may first increase with the lengthening of rainy season until reaching an “optimal rainy season length,” after which tree fraction decreases with the further lengthening of rainy season. This nonlinear response is resulted from compound mechanisms of hydrological cycle, fire, and other factors. We conclude that African savannas and deciduous woodlands have distinctive responses in their phenology and ecosystem functioning to rainy season. Further research is needed to address interaction between groundwater and tropical woodland as well as to explicitly consider the ecological significance of rainy season length under climate change.

Effects of Deforestation on Spatiotemporal Distributions of Precipitation in South America

AbstractThis study investigates how future deforestation in the Amazon may alter precipitation statistics in South America using a variable-resolution GCM. The model’s grid mesh is set up to cover South America and nearby oceans at mesoscale (25 km) resolution, and then to gradually coarsen and cover the rest of the world at 200-km resolution. Because of the computational efficiency of this approach, it was possible to carry out the first decadal-scale simulations of Amazon deforestation at mesoscale resolution. Unlike traditional mesoscale models, this approach does not require lateral boundary conditions. The results indicate that deforestation reduces simulated precipitation in the Amazon, but this reduction is much smaller than that seen in most previous GCM studies. Furthermore, a subcontinental redistribution of precipitation is found whereby the northwest Amazon becomes drier and the southeast Amazon becomes wetter. During most of the year, these changes are driven by changes in the mean intensity ...

Simulated Changes in Northwest U.S. Climate in Response to Amazon Deforestation

AbstractNumerical models have long predicted that the deforestation of the Amazon would lead to large regional changes in precipitation and temperature, but the extratropical effects of deforestation have been a matter of controversy. This paper investigates the simulated impacts of deforestation on the northwest United States December–February climate. Integrations are carried out using the Ocean–Land–Atmosphere Model (OLAM), here run as a variable-resolution atmospheric GCM, configured with three alternative horizontal grid meshes: 1) 25-km characteristic length scale (CLS) over the United States, 50-km CLS over the Andes and Amazon, and 200-km CLS in the far-field; 2) 50-km CLS over the United States, 50-km CLS over the Andes and Amazon, and 200-km CLS in the far-field; and 3) 200-km CLS globally. In the high-resolution simulations, deforestation causes a redistribution of precipitation within the Amazon, accompanied by vorticity and thermal anomalies. These anomalies set up Rossby waves that propagate...

Simulated impacts of insect defoliation on forest carbon dynamics

Many temperate and boreal forests are subject to insect epidemics. In the eastern US, over 41 million meters squared of tree basal area are thought to be at risk of gypsy moth defoliation. However, the decadal-to-century scale implications of defoliation events for ecosystem carbon dynamics are not well understood. In this study, the effects of defoliation intensity, periodicity and spatial pattern on the carbon cycle are investigated in a set of idealized model simulations. A mechanistic terrestrial biosphere model, ecosystem demography model 2, is driven with observations from a xeric oak‐pine forest located in the New Jersey Pine Barrens. Simulations indicate that net ecosystem productivity (equal to photosynthesis minus respiration) decreases linearly with increasing defoliation intensity. However, because of interactions between defoliation and drought effects, aboveground biomass exhibits a nonlinear decrease with increasing defoliation intensity. The ecosystem responds strongly with both reduced productivity and biomass loss when defoliation periodicity varies from 5 to 15 yr, but exhibits a relatively weak response when defoliation periodicity varies from 15 to 60 yr. Simulations of spatially heterogeneous defoliation resulted in markedly smaller carbon stocks than simulations with spatially homogeneous defoliation. These results show that gypsy moth defoliation has a large effect on oak‐pine forest biomass dynamics, functioning and its capacity to act as a carbon sink.

An active atmospheric methane sink in high Arctic mineral cryosols

Methane (CH4) emission by carbon-rich cryosols at the high latitudes in Northern Hemisphere has been studied extensively. In contrast, data on the CH4 emission potential of carbon-poor cryosols is limited, despite their spatial predominance. This work employs CH4 flux measurements in the field and under laboratory conditions to show that the mineral cryosols at Axel Heiberg Island in the Canadian high Arctic consistently consume atmospheric CH4. Omics analyses present the first molecular evidence of active atmospheric CH4-oxidizing bacteria (atmMOB) in permafrost-affected cryosols, with the prevalent atmMOB genotype in our acidic mineral cryosols being closely related to Upland Soil Cluster α. The atmospheric (atm) CH4 uptake at the study site increases with ground temperature between 0 °C and 18 °C. Consequently, the atm CH4 sink strength is predicted to increase by a factor of 5–30 as the Arctic warms by 5–15 °C over a century. We demonstrate that acidic mineral cryosols are a previously unrecognized potential of CH4 sink that requires further investigation to determine its potential impact on larger scales. This study also calls attention to the poleward distribution of atmMOB, as well as to the potential influence of microbial atm CH4 oxidation, in the context of regional CH4 flux models and global warming.

Vegetation Demographics in Earth System Models: a review of progress and priorities

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. Here, we review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.

Seasonal coupling of canopy structure and function in African tropical forests and its environmental controls

Tropical forests provide important ecosystem services in maintaining biodiversity, sequestering carbon and regulating climate regionally and globally. Climate triggers the seasonal transitions of vegetation structure and function in tropical forests. In turn, the seasonal cycles of structure and function in tropical forests feed back to the climate system through the control of land-atmosphere exchange of carbon, water and energy fluxes. Large uncertainties exist in the carbon and water budgets of tropical forests, and environmental controls on phenology are among the least understood factors. Although field studies have identified patterns in the environmental controls on local-scale species-level phenology in the tropics, there is little consensus on large-scale top-down environmental controls on whole-ecosystem seasonality. In this paper, we use both optical and microwave remote sensing to investigate the seasonality of vegetation canopy structure and function in three distinct tropical African forest types, and identify environmental triggers or controls of their variability. For most tropical forests that have a closed canopy and high leaf biomass, optical remote sensing (e.g., vegetation indices) captures canopy photosynthetic capacity (i.e., canopy function), while small-wavelength microwave remote sensing characterizes the leaf biomass and leaf water content of the upper canopy (i.e., canopy structure). Our results reveal a strong coupling of canopy structure with canopy function in the tropical deciduous forests and woody savannas, and their seasonalities are both controlled by precipitation rather than solar radiation. By contrast, tropical evergreen forests in Africa exhibit a decoupling of canopy structure from canopy function revealed by different sensors: canopy photosynthetic capacity shown by the optical remote sensing is linked to the seasonal variation of precipitation, while microwave remote sensing captures semi-annual leaf-flushing that is synchronous with peak insolation intensity at the top of the atmosphere, which is bimodal. The differential coupling of canopy structure and function in tropical forests observed from remote sensing highlights differences inherent in distinct vegetation types within the tropics that may originate in the different life histories of their respective floras. This satellite-based finding encourages more field-based studies to clarify the interpretation of these large scale patterns.