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At least 883 records · Page 49Linked to original sources

USGS2016

Chaparral

One of the most dynamic California ecosystems is chaparral. Dominated by evergreen, sclerophyllous shrubs and small trees, chaparral is the most extensive vegetation type in the state (Figure 1). The nearly impenetrable tangle of stiff branches of this unusual vegetation inhibits exploration, and as a consequence the public know little about its natural history and unique characteristics. This under-valued ecosystem is recognized instead by the threat of its extensive, high-intensity canopy-burning wildfires that characterize the dry summer and fall seasons of the state. Because urban areas frequently share borders or intermix with chaparral, societal interests often conflict with conservation of this ecosystem, and understanding its history and dynamics are a key to appreciating its importance. In this chapter we emphasize the principal structure and dynamics of this important ecosystem. The long summer rainless period has strong impacts on all organisms and, importantly, the droughts influence the fire regime that characterizes chaparral. An ecosystem currently characterized by a specific drought and wildfire regime can expect significant impacts from climate change. Because of its dominance at lower elevations, chaparral also is frequently found at or near the boundaries of urban developments and metropolitan centers. Attempts to suppress fire also affect chaparral dynamics in the long absence of fire. The conflicts between the impacts of chaparral wildfire and human life and structures has been an aspect of California’s history since the beginning, but as development encroaches ever more into chaparral regions, the conflicts have increased. Consequently, understanding this vegetation is important not only because of its significance in understanding ecological evolution and the ecological services provided by chaparral, but also because of its direct impacts on human settlements.

Book chapter↗

USGS2012

Assessment of boreal forest historical C dynamics in the Yukon River Basin: relative roles of warming and fire regime change

Carbon (C) dynamics of boreal forest ecosystems have substantial implications for efforts to mitigate the rise of atmospheric CO 2 and may be substantially influenced by warming and changing wildfire regimes. In this study we applied a large-scale ecosystem model that included dynamics of organic soil horizons and soil organic matter characteristics of multiple pools to assess forest C stock changes of the Yukon River Basin (YRB) in Alaska, USA, and Canada from 1960 through 2006, a period characterized by substantial climate warming and increases in wildfire. The model was calibrated for major forests with data from long-term research sites and evaluated using a forest inventory database. The regional assessment indicates that forest vegetation C storage increased by 46 Tg C, but that total soil C storage did not change appreciably during this period. However, further analysis suggests that C has been continuously lost from the mineral soil horizon since warming began in the 1970s, but has increased in the amorphous organic soil horizon. Based on a factorial experiment, soil C stocks would have increased by 158 Tg C if the YRB had not undergone warming and changes in fire regime. The analysis also identified that warming and changes in fire regime were approximately equivalent in their effects on soil C storage, and interactions between these two suggests that the loss of organic horizon thickness associated with increases in wildfire made deeper soil C stocks more vulnerable to loss via decomposition. Subbasin analyses indicate that C stock changes were primarily sensitive to the fraction of burned forest area within each subbasin and that boreal forest ecosystems in the YRB are currently transitioning from being sinks to sources at ∼0.7% annual area burned. We conclude that it is important for international mitigation efforts focused on controlling atmospheric CO 2 to consider how climate warming and changes in fire regime may concurrently affect the CO 2 sink strength of boreal forests. It is also important for large-scale biogeochemical and earth system models to include organic soil dynamics in applications to assess regional C dynamics of boreal forests responding to warming and changes in fire regime.

Ecological Applications↗

USGS2023

Incorporating wave climate complexity into modeling lower shoreface morphology and transport

The lower shoreface, a transitional subaqueous region extending from the seaward limit of the surf zone to beyond the closure depth, serves as a sediment reservoir and pathway in sandy beach environments over annual to millennial time scales. Despite the important role this region plays in shoreline dynamics, the morphodynamics of the lower shoreface remain poorly quantified and understood. To better understand controls on shoreface morphology, here we combine energetics-based suspended sediment transport formulae (Ortiz & Aston 2016) with empirical wave climate data to incorporate temporal complexity in modeled equilibrium profiles and sediment flux rates. The equilibrium shoreface shape computed using a full wave climate is steeper in shallower water and less steep in the deeper reaches compared to profiles computed using single wave characteristics. Using a full wave climate to simulate steady-state morphology will yield steeper profiles in shallow water. Suspended sediment transport rates also vary in direction and magnitude at different equilibrium profile depths and can potentially inform the location of morphodynamic boundaries in the shoreface. Our results reveal how infrequent storm waves affect shoreface slopes, with large events tending to drive sediment onshore in the deeper portions of the profile. This work explores a few ways to add complexity to simple energetics-based frameworks to reproduce empirical bathymetric data more accurately and provides insight toward refining coastal source-to-sink models.

Conference Paper↗

USGS2011

The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3

The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a coupled general circulation model (CM3) for the atmosphere, oceans, land, and sea ice. The goal of CM3 is to address emerging issues in climate change, including aerosol–cloud interactions, chemistry–climate interactions, and coupling between the troposphere and stratosphere. The model is also designed to serve as the physical system component of earth system models and models for decadal prediction in the near-term future—for example, through improved simulations in tropical land precipitation relative to earlier-generation GFDL models. This paper describes the dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component (AM3) of this model. Relative to GFDL AM2, AM3 includes new treatments of deep and shallow cumulus convection, cloud droplet activation by aerosols, subgrid variability of stratiform vertical velocities for droplet activation, and atmospheric chemistry driven by emissions with advective, convective, and turbulent transport. AM3 employs a cubed-sphere implementation of a finite-volume dynamical core and is coupled to LM3, a new land model with ecosystem dynamics and hydrology. Its horizontal resolution is approximately 200 km, and its vertical resolution ranges approximately from 70 m near the earth’s surface to 1 to 1.5 km near the tropopause and 3 to 4 km in much of the stratosphere. Most basic circulation features in AM3 are simulated as realistically, or more so, as in AM2. In particular, dry biases have been reduced over South America. In coupled mode, the simulation of Arctic sea ice concentration has improved. AM3 aerosol optical depths, scattering properties, and surface clear-sky downward shortwave radiation are more realistic than in AM2. The simulation of marine stratocumulus decks remains problematic, as in AM2. The most intense 0.2% of precipitation rates occur less frequently in AM3 than observed. The last two decades of the twentieth century warm in CM3 by 0.32°C relative to 1881–1920. The Climate Research Unit (CRU) and Goddard Institute for Space Studies analyses of observations show warming of 0.56° and 0.52°C, respectively, over this period. CM3 includes anthropogenic cooling by aerosol–cloud interactions, and its warming by the late twentieth century is somewhat less realistic than in CM2.1, which warmed 0.66°C but did not include aerosol–cloud interactions. The improved simulation of the direct aerosol effect (apparent in surface clear-sky downward radiation) in CM3 evidently acts in concert with its simulation of cloud–aerosol interactions to limit greenhouse gas warming.

Journal of Climate↗

USGS2021

Snowpack signals in North American tree rings

Climate change has contributed to recent declines in mountain snowpack and earlier runoff, which in turn has intensified hydrological droughts in western North America. Climate model projections suggest that continued and severe snowpack reductions are expected over the 21st century, with profound consequences for ecosystems and human welfare. Yet the current understanding of trends and variability in mountain snowpack is limited by the relatively short and strongly temperature forced observational record. Motivated by the urgent need to better understand snowpack dynamics in a long-term, spatially coherent framework, here we examine snow-growth relationships in western North American tree-ring chronologies. We present an extensive network of snow-sensitive proxy data to support high space/time resolution paleosnow reconstruction, quantify and interpret the type and spatial density of snow related signals in tree-ring records, and examine the potential for regional bias in the tree-ring based reconstruction of different snow drought types (dry versus warm). Our results indicate three distinct snow-growth relationships in tree-ring chronologies: moisture-limited snow proxies that include a spring temperature signal, moisture-limited snow proxies lacking a spring temperature signal, and energy-limited snow proxies. Each proxy type is based on distinct physiological tree-growth mechanisms related to topographic and climatic site conditions, and provides unique information on mountain snowpack dynamics that can be capitalized upon within a statistical reconstruction framework. This work provides a platform and foundational background required for the accelerated production of high-quality annually-resolved snowpack reconstructions from regional to high (<12 km) spatial scales in western North America, and by extension, will support an improved understanding of the vulnerability of snowmelt-derived water resources to natural variability and future climate warming.

Environmental Research Letters↗

USGS1999

Modeling the effects of land use and climate change on riverine smallmouth bass

Anthropogenic changes in temperature and stream flow, associated with watershed land use and climate change, are critical influences on the distribution and abundance of riverine fishes. To project the effects of changing land use and climate, we modeled a smallmouth bass ( Micropterus dolomieu ) population in a midwestern USA, large river–floodplain ecosystem under historical (1915–1925), present (1977–1990), and future (2060, influenced by climate change) temperature and flow regimes. The age-structured model included parameters for temperature and river discharge during critical seasonal periods, fish population dynamics, and fishing harvest. Model relationships were developed from empirical field data collected over a 13-yr period. Sensitivity analyses indicated that discharge during the spawning/rearing period had a greater effect on adult density and fishing yield than did spawning/rearing temperature or winter discharge. Simulations for 100 years projected a 139% greater mean fish density under a historical flow regime (64.9 fish/ha) than that estimated for the present (27.1 fish/ha) with a sustainable fishing harvest under both flow regimes. Simulations under future climate-change-induced temperature and flow regimes with present land use projected a 69% decrease in mean fish density (8.5 fish/ha) from present and an unstable population that went extinct during 56% of the simulations. However, when simulated under a future climate-altered temperature and flow regime with historical land use, the population increased by 66% (45.0 fish/ha) from present and sustained a harvest. Our findings suggest that land-use changes may be a greater detriment to riverine fishes than projected climate change and that the combined effects of both factors may lead to local species extinction. However, the negative effects of increased temperature and precipitation associated with future global warming could be mitigated by river channel, floodplain, and watershed restoration.

Ecological Applications↗

USGS2004

Exploitation dynamics of small fish stocks like Arctic cisco

Potential impacts to the Arctic cisco population fall into both demographic and behavioral categories. Possible demographic impacts include stock recruitment effects, limited escapement into marine habitats, and variable age-class reproductive success. Potential behavioral impacts involve migratory patterns, variable life histories, and strategies for seasonal feeding. Arctic cisco stocks are highly susceptible to over-exploitation due to our limited basic knowledge of the highly variable Arctic environment and the role they play in this dynamic ecosystem. Our knowledge of potential demographic changes is very limited, and it is necessary to determine the abundance and recruitment of the hypothesized Mackenzie River source population, the extent of the coastal migratory corridor, growth patterns, and coastal upwelling and mixing effects on population dynamics for this species. Information needed to answer some of the demographic questions includes basic evolutionary history and molecular genetics of Arctic cisco (for instance, are there contributions to the Arctic cisco stock from the Yukon?), what is the effective population size (i.e., breeding population size), and potential links to changes in climate. The basic behavioral questions include migratory and variable life history questions. For instance, the extent of movement back and forth between freshwater and the sea, age-specific differences in food web dynamics, and nearshore brackish and high salinity habitats are topics that should be studied. Life history data should be gathered to understand the variation in age at reproduction, salinity tolerance, scale and duration of the freshwater stage, survival, and adult migration. Both molecular and ecological tools should be integrated to manage the Arctic cisco stock(s), such as understanding global climate changes on patterns of harvest and recruitment, and the genetics of population structure and colonization. Perhaps other populations are contributing to the population within the Colville River other than only the Mackenzie River population. This needs further exploration. By examining otolith microchemistry, unique transitions from freshwater to sea can be identified for these stocks. This may shed light on why some fish arrive at the mouth of the Colville River, while others don’t.

Conference Paper↗

USGS2022

Crowding, climate, and the case for social distancing among trees

In an emerging era of megadisturbance, bolstering forest resilience to wildfire, insects, and drought has become a central objective in many western forests. Climate has received considerable attention as a driver of these disturbances, but few studies have examined the complexities of climate–vegetation–disturbance interactions. Current strategies for creating resilient forests often rely on retrospective approaches, seeking to impart resilience by restoring historical conditions to contemporary landscapes, but historical conditions are becoming increasingly unattainable amidst modern bioclimatic conditions. What becomes an appropriate benchmark for resilience when we have novel forests, rapidly changing climate, and unprecedented disturbance regimes? We combined two longitudinal datasets—each representing some of the most comprehensive spatially explicit, annual tree mortality data in existence—in a post-hoc factorial design to examine the nonlinear relationships between fire, climate, forest spatial structure, and bark beetles. We found that while prefire drought elevated mortality risk, advantageous local neighborhoods could offset these effects. Surprisingly, mortality risk ( P m ) was higher in crowded local neighborhoods that burned in wet years ( P m = 42%) compared with sparse neighborhoods that burned during drought ( P m = 30%). Risk of beetle attack was also increased by drought, but lower conspecific crowding impeded the otherwise positive interaction between fire and beetle attack. Antecedent fire increased drought-related mortality over short timespans (<7 years) but reduced mortality over longer intervals. These results clarify interacting disturbance dynamics and provide a mechanistic underpinning for forest restoration strategies. Importantly, they demonstrate the potential for managed fire and silvicultural strategies to offset climate effects and bolster resilience to fire, beetles, and drought.

California↗

USGS2022

Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics

Mounting evidence indicates dryland ecosystems play an important role in driving the interannual variability and trend of the terrestrial carbon sink. Nevertheless, our understanding of the seasonal dynamics of dryland ecosystem carbon uptake through photosynthesis [gross primary productivity (GPP)] remains relatively limited due in part to the limited availability of long-term data and unique challenges associated with satellite remote sensing across dryland ecosystems. Here, we comprehensively evaluated longstanding and emerging satellite vegetation proxies in their ability to capture seasonal dryland GPP dynamics. Specifically, we evaluated: 1) reflectance-based proxies normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), near infrared reflectance index (NIR v ), and kernel NDVI (kNDVI) from the MODerate resolution Imaging Spectroradiometer (MODIS); and 2) newly available physiologically-based proxy solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI). As a performance benchmark, we used GPP estimates from a robust network of 21 western United States eddy covariance tower sites that span representative gradients in dryland ecosystem climate and functional composition. We found that NIR v and SIF were the best performing GPP proxies and captured complementary aspects of seasonal GPP dynamics across dryland ecosystem types. NIR v offered better performance than the other proxies across relatively low-productivity, sparsely non-evergreen vegetated sites (R 2 = 0.59 ± 0.13); whereas SIF best captured seasonal dynamics across relatively high-productivity sites, including evergreen-dominated sites (R 2 = 0.74 ± 0.07). Notably, across grass-dominated sites, all reflectance-based proxies (NDVI, SAVI, NIR v and kNDVI) showed significant seasonal bias (hysteresis) that strengthened with the total fraction of woody vegetation cover, likely due to seasonal patterns in woody vegetation reflectance that are unrelated to or decoupled from GPP. Future efforts to fully integrate the complementary strengths of NIR v and SIF could significantly improve our understanding and representation of dryland GPP dynamics in satellite-based models.

Arizona, California, Colorado, Idaho, New Mexico, ↗

USGS2019

Ecological and management implications of climate change induced shifts in phenology of coastal fish and wildlife species in the Northeast CASC region

Climate change is causing species to shift their phenology, or the timing of recurring life events such as migration and reproduction, in variable and complex ways. This can potentially result in mismatches or asynchronies in food and habitat resources that negatively impact individual fitness, population dynamics, and ecosystem function. Numerous studies have evaluated phenological shifts in terrestrial species, particularly birds and plants, yet far fewer evaluations have been conducted for marine animals. This project seeks to improve our understanding of shifts in the timing of seasonal migration, spawning or breeding, and biological development (i.e. life stages present, dominant) of coastal fishes, marine mammals,and migratory shore and seabirds along the U.S Atlantic coast. Ideally the suite of species selected will allow us to compare whether fish, marine mammals, shore and seabird predators are shifting their phenology at different rates than their primary prey and optimal habitat conditions, thus influencing trophic interactions and population dynamics. A comprehensive literature review will be conducted simultaneous to data collection and synthesis to determine what is known, and what knowledge/information/data gaps exist regarding regional phenological responses of coastal species to climate change. Project results will help managers assess the vulnerability of coastal species to climate change by providing information on how they are responding to impacts in the region.

Conference Paper↗

USGS2023

Investigating permafrost carbon dynamics in Alaska with artificial intelligence

Positive feedbacks between permafrost degradation and the release of soil carbon into the atmosphere impact land–atmosphere interactions, disrupt the global carbon cycle, and accelerate climate change. The widespread distribution of thawing permafrost is causing a cascade of geophysical and biochemical disturbances with global impacts. Currently, few earth system models account for permafrost carbon feedback (PCF) mechanisms. This research study integrates artificial intelligence (AI) tools and information derived from field-scale surveys across the tundra and boreal landscapes in Alaska. We identify and interpret the permafrost carbon cycling links and feedback sensitivities with GeoCryoAI, a hybridized multimodal deep learning (DL) architecture of stacked convolutionally layered, memory-encoded recurrent neural networks (NN). This framework integrates in-situ measurements and flux tower observations for teacher forcing and model training. Preliminary experiments to quantify, validate, and forecast permafrost degradation and carbon efflux across Alaska demonstrate the fidelity of this data-driven architecture. More specifically, GeoCryoAI logs the ecological memory and effectively learns covariate dynamics while demonstrating an aptitude to simulate and forecast PCF dynamics—active layer thickness (ALT), carbon dioxide flux (CO 2 ), and methane flux (CH 4 )—with high precision and minimal loss (i.e. ALT RMSE : 1.327 cm [1969–2022]; CO 2 RMSE : 0.697 µ molCO 2 m −2 s −1 [2003–2021]; CH 4 RMSE : 0.715 nmolCH 4 m −2 s −1 [2011–2022]). ALT variability is a sensitive harbinger of change, a unique signal characterizing the PCF, and our model is the first characterization of these dynamics across space and time.

Alaska↗

USGS2026

Cyanobacteria and aquatic ecosystem dynamics across 28,000 years of environmental changes in subtropical North America

Ecological pressures on aquatic ecosystems have increased over recent centuries due to human activities and climate change. However, contextualizing ecosystem deterioration is often challenging due to limited knowledge of environmental changes over millennial timescales. Subtropical Carolina bays in North Carolina, USA, have remained unglaciated, preserving paleolimnological records that extend back to the last glacial period. Here, we analyzed a sediment core from the ecologically rich Lake Waccamaw spanning more than 28,000 years for aquatic proxies of nutrients, photosynthetic pigments, cyanotoxins, carbon isotopes, and terrestrial proxies of pollen and charcoal. The study explored paleolimnological changes in the aquatic environment connected to land changes and climate during the late Quaternary in the southeastern Atlantic Coastal Plain. Results reveal that while current levels of colonial cyanobacteria are high, past levels of cyanobacteria, other primary producers, and cyanotoxins were higher under natural climate variability. Abrupt ecosystem responses to increasing trophic conditions during Interstadial 3 (27.8–26.4 cal ka BP) and the early Holocene (11.4–7 cal ka BP) were marked by increases in primary producer abundance, deciduous vegetation expansion, and fire activity. Cyanobacteria remained dominant throughout the record, with colonial forms prevailing during the Holocene. Increases in pigment concentrations aligned with Quercus and were primarily driven by hydroclimatic variability and nutrient stoichiometry. Transitions between Pinus and Quercus pollen matched stadials and interstadials in the δ 18 Ο record from the North Greenland Ice Core Project (NGRIP). This study highlights the value of multi-proxy millennial-scale paleolimnological records for understanding aquatic ecosystem responses to climate conditions during the late Pleistocene.

North Carolina↗

USGS2016

Dissolved organic matter composition of Arctic rivers: Linking permafrost and parent material to riverine carbon

Recent climate change in the Arctic is driving permafrost thaw, which has important implications for regional hydrology and global carbon dynamics. Permafrost is an important control on groundwater dynamics and the amount and chemical composition of dissolved organic matter (DOM) transported by high-latitude rivers. The consequences of permafrost thaw for riverine DOM dynamics will likely vary across space and time, due in part to spatial variation in ecosystem properties in Arctic watersheds. Here we examined watershed controls on DOM composition in 69 streams and rivers draining heterogeneous landscapes across a broad region of Arctic Alaska. We characterized DOM using bulk dissolved organic carbon (DOC) concentration, optical properties, and chemical fractionation and classified watersheds based on permafrost characteristics (mapping of parent material and ground ice content, modeling of thermal state) and ecotypes. Parent material and ground ice content significantly affected the amount and composition of DOM. DOC concentrations were higher in watersheds underlain by fine-grained loess compared to watersheds underlain by coarse-grained sand or shallow bedrock. DOC concentration was also higher in rivers draining ice-rich landscapes compared to rivers draining ice-poor landscapes. Similarly, specific ultraviolet absorbance (SUVA 254 , an index of DOM aromaticity) values were highest in watersheds underlain by fine-grained deposits or ice-rich permafrost. We also observed differences in hydrophobic organic acids, hydrophilic compounds, and DOM fluorescence across watersheds. Both DOC concentration and SUVA 254 were negatively correlated with watershed active layer thickness, as determined by high-resolution permafrost modeling. Together, these findings highlight how spatial variations in permafrost physical and thermal properties can influence riverine DOM.

Global Biogeochemical Cycles↗

USGS2013

Representing the effects of alpine grassland vegetation cover on the simulation of soil thermal dynamics by ecosystem models applied to the Qinghai-Tibetan Plateau

Soil surface temperature is a critical boundary condition for the simulation of soil temperature by environmental models. It is influenced by atmospheric and soil conditions and by vegetation cover. In sophisticated land surface models, it is simulated iteratively by solving surface energy budget equations. In ecosystem, permafrost, and hydrology models, the consideration of soil surface temperature is generally simple. In this study, we developed a methodology for representing the effects of vegetation cover and atmospheric factors on the estimation of soil surface temperature for alpine grassland ecosystems on the Qinghai-Tibetan Plateau. Our approach integrated measurements from meteorological stations with simulations from a sophisticated land surface model to develop an equation set for estimating soil surface temperature. After implementing this equation set into an ecosystem model and evaluating the performance of the ecosystem model in simulating soil temperature at different depths in the soil profile, we applied the model to simulate interactions among vegetation cover, freeze-thaw cycles, and soil erosion to demonstrate potential applications made possible through the implementation of the methodology developed in this study. Results showed that (1) to properly estimate daily soil surface temperature, algorithms should use air temperature, downward solar radiation, and vegetation cover as independent variables; (2) the equation set developed in this study performed better than soil surface temperature algorithms used in other models; and (3) the ecosystem model performed well in simulating soil temperature throughout the soil profile using the equation set developed in this study. Our application of the model indicates that the representation in ecosystem models of the effects of vegetation cover on the simulation of soil thermal dynamics has the potential to substantially improve our understanding of the vulnerability of alpine grassland ecosystems to changes in climate and grazing regimes.

Qinghai;Tibet↗

USGS2019

Methane and nitrous oxide temporal and spatial variability in two midwestern USA streams containing high nitrate concentrations

Concentrations and emissions of greenhouse gases CO 2 , CH 4 , and N 2 O commonly are examined individually in aquatic environments in which each is expected to be relatively important; however, their co-occurrence and dynamic interactions in fluvial settings could provide important information about their controlling biogeochemical processes and potential contributions to global climate change. Spatial and temporal variability of CH 4 , N 2 O, and CO 2 concentrations were measured from June 1999 to September 2003 in two nitrate-rich (40–1200 μM) streams draining agricultural land in the midwestern USA that differed ~13-fold in flow. Seasonal (biweekly), diel (hourly), and transport-oriented (reach-scale) sampling approaches were compared. Dissolved gas concentrations exceeded atmospheric equilibrium values up to 700- and 16-fold, for CH 4 and N 2 O, respectively. Mean concentrations were higher in the larger stream than in the smaller stream. In both streams, CH 4 emissions were generally higher in summer-fall and negatively correlated with flow and NO 3 − concentration while N 2 O emissions were generally higher in winter/spring and positively correlated with flow and NO 3 − . In the small stream, diel variations in the concentrations, emissions, and isotopic compositions of CH 4 , N 2 O, and NO 2 − resulted from diel variations in sources, sinks, and air-water gas exchange velocities. Seasonal mean total (CH 4 + N 2 O) area-normalized emission rates, expressed as CO 2 warming potential equivalents, were similar for the two streams, but the total reach-scale emission rate for the larger stream, including CO 2 , was about 2.9 times that of the smaller stream (131.6 vs 46.0 kg CO 2 equivalents km −1 day −1 , respectively). The CH 4 contribution to this flux was 9–28%, despite the relatively high NO 3 − and O 2 concentrations in the streams, indicating contributions from upwelling groundwater or reactions in streambed sediment.

Illinois, Indiana↗

USGS1997

The intermediate disturbance hypothesis does not explain fire and diversity pattern in fynbos

The intermediate disturbance hypothesis is a widely accepted generalization regarding patterns of species diversity, but may not hold true where fire is the disturbance. In the Mediterranean-climate shrublands of South Africa, called fynbos, fire is the most importance disturbance and a controlling factor in community dynamics. The intermediate disturbance hypothesis states that diversity will be highest at sites that have had an intermediate frequency of disturbance and will be lower at sites that have experienced very high or very low disturbance frequencies. Measures of diversity are sensitive to scale; therefore, we compared species richness for three fire regimes in South African mountain fynbos to test the intermediate disturbance hypothesis over different spatial scales from 1 m 2 to 0.1 hectares. Species diversity response to fire frequency was highly scale-dependent, but the relationship between species diversity and disturbance frequency was opposite that predicted by the intermediate disturbance hypothesis. At the largest spatial scales, species diversity was highest at the least frequently burned sites (40 years between fires) and lowest at the sites of moderate (15 to 26 years between fires) and high fire frequency (alternating four and six year fire cycle). Community heterogeneity, measured both as the slope of the species-area curve for a site and as the mean dissimilarity in species composition among subplots within a site, correlated with species diversity at the largest spatial scales. Community heterogeneity was highest at the least frequently burned sites and lowest at the sites that experienced an intermediate fire frequency.

Hottentot’s Holland Nature Reserve, Western Cape P↗

USGS2016

Radiocarbon constraints imply reduced carbon uptake by soils during the 21st century

Soil is the largest terrestrial carbon reservoir and may influence the sign and magnitude of carbon cycle-climate feedbacks. Many Earth system models (ESMs) estimate a significant soil carbon sink by 2100, yet the underlying carbon dynamics determining this response have not been systematically tested against observations. We used 14C data from 157 globally distributed soil profiles sampled to 1 m depth to show that ESMs underestimated the mean age of soil carbon by more than six-fold (430±50 years vs. 3100±1800 years). Consequently, ESMs overestimated the carbon sequestration potential of soils by nearly two-fold (40±27%). These biases suggest that ESMs must better represent carbon stabilization processes and the turnover time of slow and passive reservoirs when simulating future atmospheric CO2 dynamics.

Science↗

USGS2007

Lake-level variability and water availability in the Great Lakes

In this report, we present recorded and reconstructed (pre-historical) changes in water levels in the Great Lakes, relate them to climate changes of the past, and highlight major water-availability implications for storage, coastal ecosystems, and human activities. 'Water availability,' as conceptualized herein, includes a recognition that water must be available for human and natural uses, but the balancing of how much should be set aside for which use is not discussed. The Great Lakes Basin covers a large area of North America. The lakes capture and store great volumes of water that are critical in maintaining human activities and natural ecosystems. Water enters the lakes mostly in the form of precipitation and streamflow. Although flow through the connecting channels is a primary output from the lakes, evaporation is also a major output. Water levels in the lakes vary naturally on timescales that range from hours to millennia; storage of water in the lakes changes at the seasonal to millennial scales in response to lake-level changes. Short-term changes result from storm surges and seiches and do not affect storage. Seasonal changes are driven by differences in net basin supply during the year related to snowmelt, precipitation, and evaporation. Annual to millennial changes are driven by subtle to major climatic changes affecting both precipitation (and resulting streamflow) and evaporation. Rebounding of the Earth's surface in response to loss of the weight of melted glaciers has differentially affected water levels. Rebound rates have not been uniform across the basin, causing the hydrologic outlet of each lake to rise in elevation more rapidly than some parts of the coastlines. The result is a long-term change in lake level with respect to shoreline features that differs from site to site. The reconstructed water-level history of Lake Michigan-Huron over the past 4,700 years shows three major high phases from 2,300 to 3,300, 1,100 to 2,000, and 0 to 800 years ago. Within that record is a quasi-periodic rise and fall of about 160 ? 40 years in duration and a shorter fluctuation of 32 ? 6 years that is superimposed on the 160-year fluctuation. Recorded lake-level history from 1860 to the present falls within the longer-term pattern and appears to be a single 160-year quasi-periodic fluctuation. Independent investigations of past climate change in the basin over the long-term period of record confirm that most of these changes in lake level were responses to climatically driven changes in water balance, including lake-level highstands commonly associated with cooler climatic conditions and lows with warm climate periods. The mechanisms underlying these large hydroclimatic anomalies are not clear, but they may be related to internal dynamics of the ocean-atmosphere system or dynamical responses of the ocean-atmosphere system to variability in solar radiation or volcanic activity. The large capacities of the Great Lakes allow them to store great volumes of water. As calculated at chart datum, Lake Superior stores more water (2,900 mi3) than all the other lakes combined (2,539 mi3). Lake Michigan's storage is 1,180 mi3; Lake Huron's, 850 mi3; Lake Ontario's, 393 mi3; and Lake Erie's, 116 mi3. Seasonal lake-level changes alter storage by as much as 6 mi3 in Lake Superior and as little as 2.1 mi3 in Lake Erie. The extreme high and low lake levels measured in recorded lake-level history have altered storage by as much as 31 mi3 in Lake Michigan-Huron and as little as 9 mi3 in Lake Ontario. Diversions of water into and out of the lakes are very small compared to the total volume of water stored in the lakes. The water level of Lake Superior has been regulated since about 1914 and levels of Lake Ontario since about 1960. The range of Lake Superior water-level fluctuations and storage has not been altered greatly by regulation. However, fluctuations on Lake Ontario have been reduced from 6.6 ft preregulation

Circular↗