Effects of drainage and temperature on carbon balance of tussock tundra micrososms

We examined the importance of temperature (7°C or 15°C) and soil moisture regime (saturated or field capacity) on the carbon (C) balance of arctic tussock tundra microcosms (intact blocks of soil and vegetation) in growth chambers over an 81-day simulated growing season. We measured gaseous CO₂ exchanges, methane (CH₄) emissions, and dissolved C losses on intact blocks of tussock (Eriophorum vaginatum) and intertussock (moss-dominated). We hypothesized that under increased temperature and/or enhanced drainage, C losses from ecosystem respiration (CO₂ respired by plants and heterotrophs) would exceed gains from gross photosynthesis causing tussock tundra to become a net source of C to the atmosphere. The field capacity moisture regime caused a decrease in net CO₂ storage (NEP) in tussock tundra micrososms. This resulted from a stimulation of ecosystem respiration (probably mostly microbial) with enhanced drainage, rather than a decrease in gross photosynthesis. Elevated temperature alone had no effect on NEP because CO₂ losses from increased ecosystem respiration at elevated temperature were compensated by increased CO₂ uptake (gross photosynthesis). Although CO₂ losses from ecosystem respiration were primarily limited by drainage, CH₄ emissions, in contrast, were dependent on temperature. Furthermore, substantial dissolved C losses, especially organic C, and important microhabitat differences must be considered in estimating C balance for the tussock tundra system. As much as 20% of total C fixed in photosynthesis was lost as dissolved organic C. Tussocks stored 2x more C and emitted 5x more methane than intertussocks. In spite of the limitations of this microcosm experiment, this study has further elucidated the critical role of soil moisture regime and dissolved C losses in regulating net C balance of arctic tussock tundra.     

Species Diversity Across Nutrient Gradients: An Analysis of Resource Competition in Model Ecosystems

The capture and efficient use of limiting resources influence the competitive success of individual plant species as well as species diversity across resource gradients. In simulations, efficient nutrient acquisition or nutrient retention by species were key predictors of success when nutrients were limiting. Increased nutrient supply favored species with characteristics that improved light interception or light use. Ecological theory suggests that low diversity on fertile sites may be a consequence of competitive exclusion by one or a few species with superior light-interception characteristics. On infertile sites, competitive exclusion may be a function of superior nutrient-acquisition characteristics in species. At intermediate fertility, a shift from single-resource specialization to a balanced effort in the acquisition of multiple resources should allow for greater species diversity. Thus, a unimodal relationship between diversity and nutrient supply, vegetation biomass, or productivity is predicted. However, simulations demonstrated alternate relationships depending on the ecosystem characteristic to which diversity was compared. Diversity was greatest at intermediate total biomass but increased monotonically with net primary production and nitrogen (N) supply. The highest diversity occurred midrange on a scale of community-level leaf area to fine-root length ratios, which in the context of the model indicates that the vegetation as a whole was simultaneously limited by both N and light and that effort toward the acquisition of both resources is distributed in such a way that both resources are equally exploited. Diversity was lowered by the presence of species with a superior ability to sequester resources.     

Towards an ecological understanding of biological nitrogen fixation

Biogeochemistry - N limitation to primary production and other ecosystem processes is widespread. To understand the causes and distribution of N limitation, we must understand the controls of...     

Changes in Individual Allometry Can Lead to Species Coexistence without Niche Separation

The principle of competitive exclusion is a fundamental tenet of ecology. Commonly used competition models predict that at most only one species per limiting resource can coexist in the same environment at steady state; hence, the upper limit to species diversity depends only on the number of limiting resources and not on the rates of resource supply. We demonstrate that such model behavior is the result of both the growth and biomass turnover functions being proportional to the population biomass. We argue that at least the growth function should be a nonlinear, concave downward function of biomass. This form for the growth function should arise simply because of changes in the allometry of individuals in the population. With this change in model structure, we show that any number of species can coexist at an asymptotically stable steady state, even where there is only one limiting resource. Furthermore, if growth increases nonlinearly with biomass, the steady-state resource concentration and hence the potential for biodiversity increases as the resource supply rate increases. Received 31 August 2001; accepted 10 April 2002.     

Interactions among resource partitioning, sampling effect, and facilitation on the biodiversity effect: a modeling approach

Resource partitioning, facilitation, and sampling effect are the three mechanisms behind the biodiversity effect, which is depicted usually as the effect of plant-species richness on aboveground net primary production. These mechanisms operate simultaneously but their relative importance and interactions are difficult to unravel experimentally. Thus, niche differentiation and facilitation have been lumped together and separated from the sampling effect. Here, we propose three hypotheses about interactions among the three mechanisms and test them using a simulation model. The model simulated water movement through soil and vegetation, and net primary production mimicking the Patagonian steppe. Using the model, we created grass and shrub monocultures and mixtures, controlled root overlap and grass water-use efficiency (WUE) to simulate gradients of biodiversity, resource partitioning and facilitation. The presence of shrubs facilitated grass growth by increasing its WUE and in turn increased the sampling effect, whereas root overlap (resource partitioning) had, on average, no effect on sampling effect. Interestingly, resource partitioning and facilitation interacted so the effect of facilitation on sampling effect decreased as resource partitioning increased. Sampling effect was enhanced by the difference between the two functional groups in their efficiency in using resources. Morphological and physiological differences make one group outperform the other; once these differences were established further differences did not enhance the sampling effect. In addition, grass WUE and root overlap positively influence the biodiversity effect but showed no interactions.     

Estimating Uncertainty in Ecosystem Budget Calculations

Ecosystem nutrient budgets often report values for pools and fluxes without any indication of uncertainty, which makes it difficult to evaluate the significance of findings or make comparisons across systems. We present an example, implemented in Excel, of a Monte Carlo approach to estimating error in calculating the N content of vegetation at the Hubbard Brook Experimental Forest in New Hampshire. The total N content of trees was estimated at 847 kg ha⁻¹ with an uncertainty of 8%, expressed as the standard deviation divided by the mean (the coefficient of variation). The individual sources of uncertainty were as follows: uncertainty in allometric equations (5%), uncertainty in tissue N concentrations (3%), uncertainty due to plot variability (6%, based on a sample of 15 plots of 0.05 ha), and uncertainty due to tree diameter measurement error (0.02%). In addition to allowing estimation of uncertainty in budget estimates, this approach can be used to assess which measurements should be improved to reduce uncertainty in the calculated values. This exercise was possible because the uncertainty in the parameters and equations that we used was made available by previous researchers. It is important to provide the error statistics with regression results if they are to be used in later calculations; archiving the data makes resampling analyses possible for future researchers. When conducted using a Monte Carlo framework, the analysis of uncertainty in complex calculations does not have to be difficult and should be standard practice when constructing ecosystem budgets.     

Heterogeneity of Soils and Vegetation in an Eastern Amazonian Rain Forest: Implications for Scaling Up Biomass and Production

Transferring fine-scale ecological knowledge into an understanding of earth system processes presents a considerable challenge to ecologists. Our objective here was to identify and quantify heterogeneity of, and relationships among, vegetation and soil properties in terra firme rain forest ecosystems in eastern Amazonia and assess implications for generating regional predictions of carbon (C) exchange. Some of these properties showed considerable variation among sites; soil textures varied from 11% to 92% clay. But we did not find any significant correlations between soil characteristics (percentage clay, nitrogen [N], C, organic matter) and vegetation characteristics (leaf area index [LAI], foliar N concentration, basal area, biomass, stem density). We found some evidence for increased drought stress on the sandier sites: There was a significant correlation between soil texture and wood δ¹³C (but not with foliar δ¹³C); volumetric soil moisture was lower at sandier sites; and some canopy foliage had large, negative dawn water potentials (ψ_ld), indicating limited water availability in the rooting zone. However, at every site at least one foliage sample indicated full or nearly full rehydration, suggesting significant interspecific variability in drought vulnerability. There were significant differences in foliar δ¹⁵N among sites, but not in foliar % N, suggesting differences in N cycling but not in plant access to N. We used an ecophysiological model to examine the sensitivity of gross primary production (GPP) to observed inter- and intrasite variation in key driving variables—LAI, foliar N, and ψ_ld. The greatest sensitivity was to foliar N; standard errors on foliar N data translated into uncertainty in GPP predictions up to ±10% on sunny days and ±5% on cloudy days. Local variability in LAI had a minor influence on uncertainty, especially on sunny days. The largest observed reductions in ψ_ld reduced GPP by 4%–6%. If uncertainty in foliar N estimates is propagated into the model, then GPP estimates are not significantly different among sites. Our results suggest that water restrictions in the sandier sites are not enough to reduce production significantly and that texture is not the key control on plant access to N. Received 28 June 2001; accepted 13 March 2002.     

Urinary glycoproteins in acute leukemias: a 41 000 dalton glycoprotein follows the kinetic of cytoreduction

Glycoproteins of leukemic cells and 24-hour urinary proteins were subjected to SDS polyacrylamide gel electrophoresis followed by affinity labelling I125 with Concanavalin A, indicating glycoproteins with mannose and/or glucose carbohydrate residues. Among the cellular glycoproteins a 41 000 dalton glycoprotein appeared under induction therapy in close correlation to the reduction of leukemic cells in ALL as well as in AML.     

Ecosystem feedbacks constrain the effect of day-to-day weather variability on land–atmosphere carbon exchange

Whole-ecosystem interactions and feedbacks constrain ecosystem responses to environmental change. The effects of these constraints on responses to climate trends and extreme weather events have been well studied. Here we examine how these constraints respond to changes in day-to-day weather variability without changing the long-term mean weather. Although environmental variability is recognized as a critical factor affecting ecological function, the effects of climate change on day-to-day weather variability and the resultant impacts on ecosystem function are still poorly understood. Changes in weather variability can alter the mean rates of individual ecological processes because many processes respond non-linearly to environmental drivers. We assessed how these individual-process responses to changes in day-to-day weather variability interact with one another at an ecosystem level. We examine responses of arctic tundra to changes in weather variability using stochastic simulations of daily temperature, precipitation, and light to drive a biogeochemical model. Changes in weather variability altered ecosystem carbon, nitrogen, and phosphorus stocks and cycling rates in our model. However, responses of some processes (e.g., respiration) were inconsistent with expectations because ecosystem feedbacks can moderate, or even reverse, direct process responses to weather variability. More weather variability led to greater carbon losses from land to atmosphere; less variability led to higher carbon sequestration on land. The magnitude of modeled ecosystem response to weather variability was comparable to that predicted for the effects of climate mean trends by the end of the century.