Simulated effects of dryland cropping intensification on soil organic matter and greenhouse gas exchanges using the DAYCENT ecosystem model

We present evidence to show that DAYCENT can reliably simulate soil C levels, crop yields, and annual trace gas fluxes for various soils. DAYCENT was applied to compare the net greenhouse gas fluxes for soils under different land uses. To calculate net greenhouse gas flux we accounted for changes in soil organic C, the C equivalents of N2O emissions and CH4 uptake, and the CO2 costs of N fertilizer production. Model results and data show that dryland soils that are depleted of C due to conventional till winter wheat fallow cropping can store C upon conversion to no till, by reducing the fallow period, or by reversion to native vegetation. However, model results suggest that dryland agricultural soils will still be net sources of greenhouse gases although the magnitude of the source can be significantly reduced and yields can be increased upon conversion to no till annual cropping.     

Ecosystem Impacts of Geoengineering: A Review for Developing a Science Plan

Geoengineering methods are intended to reduce climate change, which is already having demonstrable effects on ecosystem structure and functioning in some regions. Two types of geoengineering activities that have been proposed are: carbon dioxide (CO(2)) removal (CDR), which removes CO(2) from the atmosphere, and solar radiation management (SRM, or sunlight reflection methods), which reflects a small percentage of sunlight back into space to offset warming from greenhouse gases (GHGs). Current research suggests that SRM or CDR might diminish the impacts of climate change on ecosystems by reducing changes in temperature and precipitation. However, sudden cessation of SRM would exacerbate the climate effects on ecosystems, and some CDR might interfere with oceanic and terrestrial ecosystem processes. The many risks and uncertainties associated with these new kinds of purposeful perturbations to the Earth system are not well understood and require cautious and comprehensive research.     

Responses of soil microbial communities to water stress: results from a meta-analysis

Soil heterotrophic respiration and nutrient mineralization are strongly affected by environmental conditions, in particular by moisture fluctuations triggered by rainfall events. When soil moisture decreases, so does decomposers' activity, with microfauna generally undergoing stress sooner than bacteria and fungi. Despite differences in the responses of individual decomposer groups to moisture availability (e.g., bacteria are typically more sensitive than fungi to water stress), we show that responses of decomposers at the community level are different in soils and surface litter, but similar across biomes and climates. This results in a nearly constant soil-moisture threshold corresponding to the point when biological activity ceases, at a water potential of about -14 MPa in mineral soils and -36 MPa in surface litter. This threshold is shown to be comparable to the soil moisture value where solute diffusion becomes strongly inhibited in soil, while in litter it is dehydration rather than diffusion that likely limits biological activity around the stress point. Because of these intrinsic constraints and lack of adaptation to different hydro-climatic regimes, changes in rainfall patterns (primary drivers of the soil moisture balance) may have dramatic impacts on soil carbon and nutrient cycling.     

Sinks for nitrogen inputs in terrestrial ecosystems: a meta-analysis of 15N tracer field studies

Effects of anthropogenic nitrogen (N) deposition and the ability of terrestrial ecosystems to store carbon (C) depend in part on the amount of N retained in the system and its partitioning among plant and soil pools. We conducted a meta-analysis of studies at 48 sites across four continents that used enriched 15N isotope tracers in order to synthesize information about total ecosystem N retention (i.e., total ecosystem 15N recovery in plant and soil pools) across natural systems and N partitioning among ecosystem pools. The greatest recoveries of ecosystem 15N tracer occurred in shrublands (mean, 89.5%) and wetlands (84.8%) followed by forests (74.9%) and grasslands (51.8%). In the short term (< 1 week after 15N tracer application), total ecosystem 15N recovery was negatively correlated with fine-root and soil 15N natural abundance, and organic soil C and N concentration but was positively correlated with mean annual temperature and mineral soil C:N. In the longer term (3-18 months after 15N tracer application), total ecosystem 15N retention was negatively correlated with foliar natural-abundance 15N but was positively correlated with mineral soil C and N concentration and C:N, showing that plant and soil natural-abundance 15N and soil C:N are good indicators of total ecosystem N retention. Foliar N concentration was not significantly related to ecosystem 15N tracer recovery, suggesting that plant N status is not a good predictor of total ecosystem N retention. Because the largest ecosystem sinks for 15N tracer were below ground in forests, shrublands, and grasslands, we conclude that growth enhancement and potential for increased C storage in aboveground biomass from atmospheric N deposition is likely to be modest in these ecosystems. Total ecosystem 15N recovery decreased with N fertilization, with an apparent threshold fertilization rate of 46 kg N x ha(-1) x yr(-1) above which most ecosystems showed net losses of applied 15N tracer in response to N fertilizer addition.     

Microbial stress-response physiology and its implications for ecosystem function

Microorganisms have a variety of evolutionary adaptations and physiological acclimation mechanisms that allow them to survive and remain active in the face of environmental stress. Physiological responses to stress have costs at the organismal level that can result in altered ecosystem-level C, energy, and nutrient flows. These large-scale impacts result from direct effects on active microbes' physiology and by controlling the composition of the active microbial community. We first consider some general aspects of how microbes experience environmental stresses and how they respond to them. We then discuss the impacts of two important ecosystem-level stressors, drought and freezing, on microbial physiology and community composition. Even when microbial community response to stress is limited, the physiological costs imposed on soil microbes are large enough that they may cause large shifts in the allocation and fate of C and N. For example, for microbes to synthesize the osmolytes they need to survive a single drought episode they may consume up to 5% of total annual net primary production in grassland ecosystems, while acclimating to freezing conditions switches Arctic tundra soils from immobilizing N during the growing season to mineralizing it during the winter. We suggest that more effectively integrating microbial ecology into ecosystem ecology will require a more complete integration of microbial physiological ecology, population biology, and process ecology.     

Sustainability or collapse: what can we learn from integrating the history of humans and the rest of nature?

Understanding the history of how humans have interacted with the rest of nature can help clarify the options for managing our increasingly interconnected global system. Simple, deterministic relationships between environmental stress and social change are inadequate. Extreme drought, for instance, triggered both social collapse and ingenious management of water through irrigation. Human responses to change, in turn, feed into climate and ecological systems, producing a complex web of multidirectional connections in time and space. Integrated records of the co-evolving human-environment system over millennia are needed to provide a basis for a deeper understanding of the present and for forecasting the future. This requires the major task of assembling and integrating regional and global historical, archaeological, and paleoenvironmental records. Humans cannot predict the future. But, if we can adequately understand the past, we can use that understanding to influence our decisions and to create a better, more sustainable and desirable future.