R. B. Cook

Participatory design of DataONE—Enabling cyberinfrastructure for the biological and environmental sciences

Abstract The scope and nature of biological and environmental research are evolving in response to environmental challenges such as global climate change, invasive species and emergent diseases. In particular, scientific studies are increasingly focusing on long-term, broad-scale, and complex questions that require massive amounts of diverse data collected by remote sensing platforms and embedded environmental sensor networks; collaborative, interdisciplinary science teams; and new approaches for managing, preserving, analyzing, and sharing data. Here, we describe the design of DataONE (Data Observation Network for Earth)—a cyberinfrastructure platform developed to support rapid data discovery and access across diverse data centers distributed worldwide and designed to provide scientists with an integrated set of familiar tools that support all elements of the data life cycle (e.g., from planning and acquisition through data integration, analysis and visualization). Ongoing evolution of the DataONE architecture is based on participatory, user-centered design processes including: (1) identification and prioritization of stakeholder communities; (2) developing an understanding of their perceptions, attitudes and user requirements; (3) usability analysis and assessment; and (4) engaging science teams in grand challenge exemplars such as understanding the broad-scale dynamics of bird migration. In combination, the four approaches engage the broad community in providing guidance on infrastructure design and implementation.

Global patterns and controls of soil organic carbon dynamics as simulated by multiple terrestrial biosphere models: Current status and future directions

Abstract Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and C loss from soil accounts for a large proportion of land‐atmosphere C exchange. Therefore, a small change in soil organic C (SOC) can affect atmospheric carbon dioxide (CO2) concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil C exchange with the atmosphere through site measurements, inventories, and empirical/process‐based modeling. However, these estimates are highly uncertain, and identifying major driving forces controlling soil C dynamics remains a key research challenge. This study has compiled century‐long (1901–2010) estimates of SOC storage and heterotrophic respiration (Rh) from 10 terrestrial biosphere models (TBMs) in the Multi‐scale Synthesis and Terrestrial Model Intercomparison Project and two observation‐based data sets. The 10 TBM ensemble shows that global SOC estimate ranges from 425 to 2111 Pg C (1 Pg = 1015 g) with a median value of 1158 Pg C in 2010. The models estimate a broad range of Rh from 35 to 69 Pg C yr−1 with a median value of 51 Pg C yr−1 during 2001–2010. The largest uncertainty in SOC stocks exists in the 40–65°N latitude whereas the largest cross‐model divergence in Rh are in the tropics. The modeled SOC change during 1901–2010 ranges from −70 Pg C to 86 Pg C, but in some models the SOC change has a different sign from the change of total C stock, implying very different contribution of vegetation and soil pools in determining the terrestrial C budget among models. The model ensemble‐estimated mean residence time of SOC shows a reduction of 3.4 years over the past century, which accelerate C cycling through the land biosphere. All the models agreed that climate and land use changes decreased SOC stocks, while elevated atmospheric CO2 and nitrogen deposition over intact ecosystems increased SOC stocks—even though the responses varied significantly among models. Model representations of temperature and moisture sensitivity, nutrient limitation, and land use partially explain the divergent estimates of global SOC stocks and soil C fluxes in this study. In addition, a major source of systematic error in model estimations relates to nonmodeled SOC storage in wetlands and peatlands, as well as to old C storage in deep soil layers.

Disentangling climatic and anthropogenic controls on global terrestrial evapotranspiration trends

We examined natural and anthropogenic controls on terrestrial evapotranspiration (ET) changes from 1982 to 2010 using multiple estimates from remote sensing-based datasets and process-oriented land surface models. A significant increasing trend of ET in each hemisphere was consistently revealed by observationally-constrained data and multi-model ensembles that considered historic natural and anthropogenic drivers. The climate impacts were simulated to determine the spatiotemporal variations in ET. Globally, rising CO2 ranked second in these models after the predominant climatic influences, and yielded decreasing trends in canopy transpiration and ET, especially for tropical forests and high-latitude shrub land. Increasing nitrogen deposition slightly amplified global ET via enhanced plant growth. Land-use-induced ET responses, albeit with substantial uncertainties across the factorial analysis, were minor globally, but pronounced locally, particularly over regions with intensive land-cover changes. Our study highlights the importance of employing multi-stream ET and ET-component estimates to quantify the strengthening anthropogenic fingerprint in the global hydrologic cycle.

Impact of large‐scale climate extremes on biospheric carbon fluxes: An intercomparison based on MsTMIP data

Understanding the role of climate extremes and their impact on the carbon (C) cycle is increasingly a focus of Earth system science. Climate extremes such as droughts, heat waves, or heavy precipitation events can cause substantial changes in terrestrial C fluxes. On the other hand, extreme changes in C fluxes are often, but not always, driven by extreme climate conditions. Here we present an analysis of how extremes in temperature and precipitation, and extreme changes in terrestrial C fluxes are related to each other in 10 state-of-the-art terrestrial carbon models, all driven by the same climate forcing. We use model outputs from the North American Carbon Program Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP). A global-scale analysis shows that both droughts and heat waves translate into anomalous net releases of CO2 from the land surface via different mechanisms: Droughts largely decrease gross primary production (GPP) and to a lower extent total respiration (TR), while heat waves slightly decrease GPP but increase TR. Cold and wet periods have a smaller opposite effect. Analyzing extremes in C fluxes reveals that extreme changes in GPP and TR are often caused by strong shifts in water availability, but for extremes in TR shifts in temperature are also important. Extremes in net CO2 exchange are equally strongly driven by deviations in temperature and precipitation. Models mostly agree on the sign of the C flux response to climate extremes, but model spread is large. In tropical forests, C cycle extremes are driven by water availability, whereas in boreal forests temperature plays a more important role. Models are particularly uncertain about the C flux response to extreme heat in boreal forests.

Global patterns of drought recovery.

Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time—how long an ecosystem requires to revert to its pre-drought functional state—is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth’s climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.

Chemical limnology of soft water lakes in the Upper Midwest

Water samples from 36 lakes in northern Minnesota, Wisconsin, and Michigan were collected and analyzed during 1983–1984. All study lakes were dilute and had total alkalinities of less than 150 μeq · L−1. Minnesota lakes have hydrologic inputs from the watershed and inputs of base cations derived from the watershed. Study lakes in Minnesota had higher total alkalinities, dissolved organic carbon, and noncarbonate alkalinity as a result of watershed inputs. Lakes in Michigan and Wisconsin were precipitation-dominated seepage lakes that have lower concentrations of base cations than lakes in Minnesota. All of the study lakes have lower sulfate concentrations than expected, based on atmospheric wet deposition and evapotranspiration.Pore water samples collected from one of the study lakes—Little Rock Lake—in Wisconsin were used to calculate diffusive fluxes between the sediment and water column. According to these calculations, the sediments were a source of total alkalinity and Ca2+ and a sink for SO42−. The sediment-water exchange of total alkalinity, Ca2+, and SO42− appears to be important in the whole-lake budgets of these ions for Little Rock Lake.

Paleoecological investigation of recent lake acidification in the northern Great Lakes states

Paleoecological analyses of sediments from nine northern Great Lakes states (NGLS) lakes reveal small pH changes in seven of these lakes since 1860, four of these being declines. The largest diatom-inferred (DI) pH declines of 0.5 pH units were found in Brown L. and Denton L., Wisconsin. Two other lakes with suspected total alkalinity declines (based on an acidification model and on historical water chemistry, respectively), McNearney L., Michigan, and Camp 12 L., Wisconsin, have not acidified recently according to diatom-inference techniques. Many of the observed trends of increasing pH are coincident with logging; floristic composition of diatom assemblages also changed coincident with fisheries manipulations in some lakes, but these floristic trends did not affect DI pH. Sediment core profiles of Pb, S, and polycyclic aromatic hydrocarbons provide a record of atmospheric deposition of fossil fuel combustion products beginning around the turn of the century; onset is later and accumulation rates are smaller than for other northeastern study regions of the Paleoecological Investigation of Recent Lake Acidification (PIRLA) Project. The response of diatom species to lakewater pH in the NGLS region is very strong and similar to response in other regions. Overall, there is little paleoecological evidence that acidic deposition has caused significant acidification of lakes in the NGLS region.

Discover, visualize, and deliver geospatial data through OGC standards-based WebGIS system

Geospatial data are important to understand the Earth — ecosystem dynamics, land cover changes, resource management, and human interactions with the Earth to name a few. One of the biggest difficulties users face is to discover, access, and assemble distributed, large volume, heterogeneous geospatial data to conduct geo-analysis. Traditional methods of geospatial data discovery, visualization, and delivery lack the capabilities of resource sharing and automation across systems or organizational boundaries. They require users to download the data “as-is” in their original file format, projection, and extent. Also, discovering data served by traditional methods requires prior knowledge of data location, and processing requires specialized expertise. These drawbacks of traditional methods create additional burden to users, introduce too much overhead to research, and also reduce the potential usage of the data. At the Oak Ridge National Laboratory (ORNL), researchers working on NASA-sponsored projects: Distributed Active Archive Center (DAAC) and Modeling and Synthesis Thematic Data Center (MAST-DC) have tapped into the benefits of Open Geospatial Consortium (OGC) standards to overcome the drawbacks of traditional methods of geospatial data discovery, visualization, and delivery. The OGC standards-based approach facilitates data sharing and interoperability across network, organizational, and geopolitical boundaries. Tools and services based on OGC standards deliver the data in many user defined formats and allow users to visualize the data prior to download. This paper introduces an approach taken to visualize and deliver ORNL DAAC, MAST-DC, and other relevant geospatial data through OGC standards-based Web Services, including Web Map Service (WMS), Web Coverage Service (WCS), and Web Feature Service (WFS). It also introduces a WebGIS system built on top of OGC services that helps users discover, visualize, and access geospatial data.

Toward “optimal” integration of terrestrial biosphere models

Multimodel ensembles (MME) are commonplace in Earth system modeling. Here we perform MME integration using a 10-member ensemble of terrestrial biosphere models (TBMs) from the Multiscale synthesis and Terrestrial Model Intercomparison Project (MsTMIP). We contrast optimal (skill based for present-day carbon cycling) versus naive (“one model-one vote”) integration. MsTMIP optimal and naive mean land sink strength estimates (−1.16 versus −1.15 Pg C per annum respectively) are statistically indistinguishable. This holds also for grid cell values and extends to gross uptake, biomass, and net ecosystem productivity. TBM skill is similarly indistinguishable. The added complexity of skill-based integration does not materially change MME values. This suggests that carbon metabolism has predictability limits and/or that all models and references are misspecified. Resolving this issue requires addressing specific uncertainty types (initial conditions, structure, and references) and a change in model development paradigms currently dominant in the TBM community.

Paleolimnology of McNearney lake: an acidic lake in northern Michigan

McNearney Lake is an acidic (pH=4.4) lake in the Upper Peninsula of Michigan with low acid neutralizing capacity (ANC=-38 μeq L-1) and high SOinf4sup2-and aluminium concentrations. Oligotrophy is indicated by high Secchi transparency and by low chlorophyll a, total phosphorus, and total nitrogen concentrations. The lake water is currently acidic because base cations are supplied to the lake water at a low rate and because SOinf4sup2-from atmospheric deposition was not appreciably retained by the lake sediments or watershed and was present in the water column.This interdisciplinary paleolimnological study indicates that McNearney Lake is naturally acidic and has been so since at least 4000 years B.P., as determined from inferred-pH techniques based on contemporary diatom-pH relationships. Predicted pH values ranged from 4.7 to 5.0 over the 4000-year stratigraphy. Considerable shifts in species composition and abundance were observed in diatom stratigraphy, but present-day distributions indicate that all abundant taxa most frequently occur under acidic conditions, suggesting that factors other than pH are responsible for the shifts. The diatom-inferred pH technique as applied to McNearney Lake has too large an uncertainly and is not sensitive enough to determine the subtle recent changes in lakewater pH expected from changes in atmospheric deposition because: (1) McNearney Lake has the lowest pH in the contemporary diatom data set in the region and confidence intervals for pH predictions increase at the extremes of regressions; (2) other factors in addition to pH may be responsible for the diatom species distribution in the lake and in the entire northern Great Lakes region; (3) McNearney Lake has a well-buffered pH as a consequence of its low pH and high aluminium concentrations and is not expected to exhibit a large pH change as a result of changes in atmospheric deposition; and (4) atmospheric deposition in the region is modest and would not cause a pH shift large enough to be discernable in McNearney Lake.Elevated atmospheric deposition is indicated in recent sediments by Pb, V, and polycyclic aromatic hydrocarbon accumulation rates and to a lesser extent by those of Cu and Zn; however, these accumulation rates are substantially lower than those observed for acidified lakes in the northeastern United States. Although atmospheric loadings of materials associated with fossil fuel combustion have recently increased to McNearney Lake and apparently are continuing, the present study of the diatom subfossil record does not indicate a distinct, recent acidification (pH decrease).