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At least 865 records · Page 48Linked to original sources

USGS2025

An early Holocene wet period in the southwestern United States

Multiple generations of spring-fed streams traversed ∼800 km 2 of the Las Vegas Valley in southern Nevada between ca. 10.9 ka and 8.5 ka, depositing an extensive tufa network. The scale of this network and diversity of tufa morphologies is novel in North America and offers an opportunity to obtain quantitative paleoclimate data for the region during the early Holocene. We determined isotopic compositions and estimated past temperatures using clumped isotope data from early Holocene tufa on the valley floor (698 m) as well as tufa forming today at higher elevation in the nearby Spring Mountains at Cold Creek Spring (1856 m). Modern and fossil tufa yielded comparably low δ 18 O values, implying that source waters for both were derived from high-elevation winter precipitation. Clumped isotope temperatures of modern tufa average 15.8 ± 2.5 °C, aligning with mean summer temperatures of the emergent spring water, and indicate equilibrium conditions of tufa formation. The early Holocene tufa yielded similar clumped isotope temperatures, averaging 15.2 ± 3.9 °C, meaning it precipitated at temperatures that occur at much higher elevations today. The Las Vegas tufa record, combined with nearby and temporally correlative paleospring and lacustrine records, suggest that cool/wet conditions prevailed throughout the Mojave Desert during the early Holocene. These records also demonstrate that spring ecosystems responded to millennial-scale hydroclimate variations that supersede climate change driven solely by insolation. The previously unrecognized pattern of ecosystem response to hydroclimate documented here may assist in understanding climate drivers for the early Holocene and provide critical information for the fate of groundwater-dependent ecosystems in the southwestern United States.

Nevada↗

USGS2015

Robust global ocean cooling trend for the pre-industrial Common Era

The oceans mediate the response of global climate to natural and anthropogenic forcings. Yet for the past 2,000 years — a key interval for understanding the present and future climate response to these forcings — global sea surface temperature changes and the underlying driving mechanisms are poorly constrained. Here we present a global synthesis of sea surface temperatures for the Common Era ( CE ) derived from 57 individual marine reconstructions that meet strict quality control criteria. We observe a cooling trend from 1 to 1800 CE that is robust against explicit tests for potential biases in the reconstructions. Between 801 and 1800 CE , the surface cooling trend is qualitatively consistent with an independent synthesis of terrestrial temperature reconstructions, and with a sea surface temperature composite derived from an ensemble of climate model simulations using best estimates of past external radiative forcings. Climate simulations using single and cumulative forcings suggest that the ocean surface cooling trend from 801 to 1800 CE is not primarily a response to orbital forcing but arises from a high frequency of explosive volcanism. Our results show that repeated clusters of volcanic eruptions can induce a net negative radiative forcing that results in a centennial and global scale cooling trend via a decline in mixed-layer oceanic heat content.

Nature Geoscience↗

USGS2019

Effects of salinity and light on growth and interspecific interactions between Myriophyllum spicatum L. and Ruppia maritima L.

Submerged macrophyte habitats provide significant benefits to estuarine systems. In southeast Louisiana, Myriophyllum spicatum L. (milfoil) and Ruppia maritima L. (widgeongrass) are dominant species existing across fresh to brackish areas. Though frequently co-occurring across the range of salinity and light conditions, their individual responses to changing environmental conditions from restoration, weather and climate may determine overall species distribution, and biomass abundance. We compared milfoil and widgeongrass growth (i.e., biomass increase) across a range of salinity and light, in monoculture (salinity: 0, 5, 10, 15, 20; light: high ˜ 50% ambient; low ˜ 20% ambient), and in mixture (salinity: 0, 10, 20; light: high, low). In monoculture, milfoil growth was reduced at high salinity (20) versus low salinity (0), while biomass allocation differed significantly with greater allocation to shoots under high light, compared to low light. Widgeongrass was minimally affected by salinity, with reduced stem densities at high salinity compared to low salinity. In mixture, both species under-yielded compared to monoculture with milfoil reduced with high salinity and light, and low salinity and light; widgeongrass under-yielded with low salinity and high light, and mid salinity (10) and low light. These differences in species’ responses suggest that salinity and light contribute to the distribution of milfoil and widgeongrass, with higher salinities and light favoring widgeongrass growth, and lower light possibly decreasing both species’ growth, and ultimately, distribution. With continued changes occurring and predicted from both coastal restoration and climate change, understanding drivers of habitat forming species remains critical to inform future landscapes.

Aquatic Botany↗

USGS2021

Is the grass always greener? Land surface phenology reveals differences in peak and season-long vegetation productivity responses to climate and management

Vegetation phenology—the seasonal timing and duration of vegetative phases—is controlled by spatiotemporally variable contributions of climatic and environmental factors plus additional potential influence from human management. We used land surface phenology derived from the Advanced Very High Resolution Radiometer and climate data to examine variability in vegetation productivity and phenological dates from 1989 to 2014 in the U.S. Northwestern Plains, a region with notable spatial heterogeneity in climate, vegetation, and land use. We first analyzed interannual trends in six phenological measures as a baseline. We then demonstrated how including annual-resolution predictors can provide more nuanced insights into measures of phenology between plant communities and across the ecoregion. Across the study area, higher annual precipitation increased both peak and season-long productivity. In contrast, higher mean annual temperatures tended to increase peak productivity but for the majority of the study area decreased season-long productivity. Annual precipitation and temperature had strong explanatory power for productivity-related phenology measures but predicted date-based measures poorly. We found that relationships between climate and phenology varied across the region and among plant communities and that factors such as recovery from disturbance and anthropogenic management also contributed in certain regions. In sum, phenological measures did not respond ubiquitously nor covary in their responses. Nonclimatic dynamics can decouple phenology from climate; therefore, analyses including only interannual trends should not assume climate alone drives patterns. For example, models of areas exhibiting greening or browning should account for climate, anthropogenic influence, and natural disturbances. Investigating multiple aspects of phenology to describe growing-season dynamics provides a richer understanding of spatiotemporal patterns that can be used for predicting ecosystem responses to future climates and land-use change. Such understanding allows for clearer interpretation of results for conservation, wildlife, and land management.

Ecology and Evolution↗

USGS2024

The feasibility of using national-scale datasets for classifying wetlands in Arizona with machine learning

The advent of machine learning techniques has led to a proliferation of landscape classification products. These approaches can fill gaps in wetland inventories across the United States (U.S.) provided that large reference datasets are available to develop accurate models. In this study, we tested the feasibility of expediting the classification process by sourcing requisite training and testing data from existing national-scale land cover maps instead of customized sample sets. We created a single map of water and wetland presence by intersecting water and wetland classes from available land cover products (National Wetland Inventory, Gap Analysis Project, National Land Cover Database and Dynamic Surface Water Extent) across the U.S. state of Arizona, which has fewer wetland-specific mapping products than other parts of the U.S. We derived classified samples for four wetland classes from the combined map: open water, herbaceous wetlands, wooded wetlands and non-wetland cover. In Google Earth Engine, we developed a random forest model that combined the training data with spatial predictor variables, including vegetation greenness indices, wetness indices, seasonal index variation, topographic parameters and vegetation height metrics. Results show that the final model separates the four classes with an overall accuracy of 86.2%. The accuracy suggests that existing datasets can be effectively used to compile machine learning training samples to map wetlands in arid landscapes in the U.S. These methods hold promise for the generation of wetland inventories at more frequent intervals, which could allow more nuanced investigations of wetland change over time in response to anthropogenic and climatic drivers.

Arizona↗

USGS2021

Multivariate Bayesian clustering using covariate-informed components with application to boreal vegetation sensitivity

Climate change is impacting both the distribution and abundance of vegetation, especially in far northern latitudes. The effects of climate change are different for every plant assemblage and vary heterogeneously in both space and time. Small changes in climate could result in large vegetation responses in sensitive assemblages but weak responses in robust assemblages. But, patterns and mechanisms of sensitivity and robustness are not yet well understood, largely due to a lack of long-term measurements of climate and vegetation. Fortunately, observations are sometimes available across a broad spatial extent. We develop a novel statistical model for a multivariate response based on unknown cluster-specific effects and covariances, where cluster labels correspond to sensitivity and robustness. Our approach utilizes a prototype model for cluster membership that offers flexibility while enforcing smoothness in cluster probabilities across sites with similar characteristics. We demonstrate our approach with an application to vegetation abundance in Alaska, USA, in which we leverage the broad spatial extent of the study area as a proxy for unrecorded historical observations. In the context of the application, our approach yields interpretable site-level cluster labels associated with assemblage-level sensitivity and robustness without requiring strong a priori assumptions about the drivers of climate sensitivity.

Alaska↗

USGS2009

USGS field activity 08FSH01 on the west Florida shelf, Gulf of Mexico, in August 2008

From August 11 to 15, 2008, a cruise led by the U.S. Geological Survey (USGS) collected air and sea surface partial pressure of carbon dioxide (pCO2), pH, dissolved inorganic carbon (DIC), and total alkalinity (TA) data on the west Florida shelf. Approximately 1,600 data points were collected underway over a 650-kilometer (km) trackline using the Multiparameter Inorganic Carbon Analyzer (MICA). The collection of data extended from Crystal River southward to Marco Island, Florida (~400 km), and westward up to 160 km off the Florida coast. Discrete water samples from approximately 40 locations were also taken at specific localities to corroborate underway data measurements. The USGS St. Petersburg Coastal and Marine Science Center (SPCMSC) assigns a unique identifier to each cruise or field activity. For example, 08FSH01 tells us the data were collected in 2008 for the Response of Florida Shelf (FSH) Ecosystems to Climate Change project, and the data were collected during the first field activity for that study in that calendar year.

Florida↗

USGS2009

USGS field activity 09FSH01 on the west Florida shelf, Gulf of Mexico, in February 2009

From February 24 to 28, 2009, a cruise led by the U.S. Geological Survey (USGS) collected air and sea surface partial pressure of carbon dioxide (pCO2), pH, dissolved inorganic carbon (DIC), and total alkalinity (TA) data on the west Florida shelf. Approximately 1,800 data points were collected underway over a 1,300-kilometer (km) trackline using the Multiparameter Inorganic Carbon Analyzer (MICA). The collection of data extended from Crystal River to Marco Island, Florida (~400 km), and westward up to 160 km off the Florida coast. Discrete water samples were also taken at specific localities to corroborate underway data measurements. The USGS St. Petersburg Coastal and Marine Science Center (SPCMSC) assigns a unique identifier to each cruise or field activity. For example, 09FSH01 tells us that the data were collected in 2009 for the Response of Florida Shelf (FSH) Ecosystems to Climate Change project, and the data were collected during the first field activity for that study in that calendar year.

Florida↗

USGS2009

USGS field activity 09FSH02 on the west Florida shelf, Gulf of Mexico, in August 2009

From August 17 to 21, 2009, a cruise led by the U.S. Geological Survey (USGS) collected air and sea surface partial pressure of carbon dioxide (pCO2), pH, dissolved inorganic carbon (DIC), and total alkalinity (TA) data on the west Florida shelf. Approximately 2,000 data points were collected underway over a 1,320-kilometer (km) track line using the Multiparameter Inorganic Carbon Analyzer (MICA). The collection of data extended from Crystal River to Marco Island, Florida (~400 km), and westward up to 160 km off the Florida coast. Discrete water samples were also taken at specific localities to corroborate underway data measurements. The USGS St. Petersburg Coastal and Marine Science Center (SPCMSC) assigns a unique identifier to each cruise or field activity. For example, 09FSH02 tells us that the data were collected in 2009 for the Response of Florida Shelf (FSH) Ecosystems to Climate Change project, and the data were collected during the second field activity for that study in that calendar year.

Florida↗

USGS2011

USGS science for the Nation's changing coasts; shoreline change assessment

The coastline of the United States features some of the most popular tourist and recreational destinations in the world and is the site of intense residential, commercial, and industrial development. The coastal zone also has extensive and pristine natural areas, with diverse ecosystems providing essential habitat and resources that support wildlife, fish, and human use. Coastal erosion is a widespread process along most open-ocean shores of the United States that affects both developed and natural coastlines. As the coast changes, there are a wide range of ways that change can affect coastal communities, habitats, and the physical characteristics of the coast?including beach erosion, shoreline retreat, land loss, and damage to infrastructure. Global climate change will likely increase the rate of coastal change. A recent study of the U.S. Mid-Atlantic coast, for example, found that it is virtually certain that sandy beaches will erode faster in the future as sea level rises because of climate change. The U.S. Geological Survey (USGS) is responsible for conducting research on coastal change hazards, understanding the processes that cause coastal change, and developing models to predict future change. To understand and adapt to shoreline change, accurate information regarding the past and present configurations of the shoreline is essential. A comprehensive, nationally consistent analysis of shoreline movement is needed. To meet this national need, the USGS is conducting an analysis of historical shoreline changes along open-ocean coasts of the conterminous United States and parts of Alaska and Hawaii, as well as the coasts of the Great Lakes.

Fact Sheet↗

USGS2023

Synthesis of climate and ecological science to support grassland management priorities in the North Central Region

Grasslands in the Great Plains are of ecological, economic, and cultural importance in the United States. In response to a need to understand how climate change and variability will impact grassland ecosystems and their management in the 21st century, the U.S. Geological Survey North Central Climate Adaptation Science Center led a synthesis of peer-reviewed climate and ecology literature relevant to grassland management in the North Central Region (including Montana, Wyoming, Colorado, North Dakota, South Dakota, Nebraska, and Kansas). This synthesis was done to begin to address grassland managers’ information needs and identify research gaps. This open-file report summarizes the impacts of climate change and variability on temperature, water availability, wildfire, vegetation, wildlife, large-bodied ruminants, grazing, and land-use change and the implications for grassland management in the North Central region. This open-file report also identifies areas in which further research is needed. U.S. Geological Survey funded this project.

Colorado, Kansas, Montana, Nebraska, North Dakota,↗

USGS2009

Planning for an uncertain future - Monitoring, integration, and adaptation

The 6.7 billion human inhabitants of the earth have the ability to drastically alter ecosystems and the populations of species that have taken eons to evolve. By better understanding how our actions affect the environment, we stand a better chance of designing successful strategies to manage ecosystems sustainably. Toward this end, the Third Interagency Conference on Research in the Watersheds (ICRW) was convened in Estes Park, CO, on September 8-11, 2008. The Conference provided a forum to present adaptive management as a practical tool for learning how to manage complex ecosystems more sustainably. Further complexity introduced by spatially variable and continuously changing environmental drivers favors this management approach because of its emphasis on adaptation in response to changing conditions or ineffective actions. For climate change in particular, an adaptive approach can more effectively accommodate the uncertainty in future climate scenarios. Scenarios compiled by the Intergovernmental Panel on Climate Change are built on distinct economic, energy, and societal models. The scenarios predict potential changes in greenhouse gases, temperature, precipitation, and atmospheric aerosols, which would have direct or indirect impacts on the timing, volume, and quality of runoff, vegetation, snowpack, stream temperature, groundwater, thawing permafrost, and icecaps. Through presentations and field trips, researchers and stakeholders described how their findings and issues fit into the adaptive management 'learning by doing' paradigm of Assess > Design > Implement > Monitor > Evaluate > Adjust > Assess.

Scientific Investigations Report↗

USGS2017

Functional traits and ecological affinities of riparian plants along the Colorado River in Grand Canyon

Trait-based approaches to vegetation analyses are becoming more prevalent in studies of riparian vegetation dynamics, including responses to flow regulation, groundwater pumping, and climate change. These analyses require species trait data compiled from the literature and floras or original field measurements. Gathering such data makes trait-based research time intensive at best and impracticable in some cases. To support trait-based analysis of vegetation along the Colorado River through Grand Canyon, a data set of 20 biological traits and ecological affinities for 179 species occurring in that study area was compiled. This diverse flora shares species with many riparian areas in the western USA and includes species that occur across a wide moisture gradient. Data were compiled from published scientific papers, unpublished reports, plant fact sheets, existing trait databases, regional floras, and plant guides. Data for ordinal environmental tolerances were more readily available than were quantitative traits. More publicly available data are needed for traits of both common and rare southwestern U.S. plant species to facilitate comprehensive, trait-based research. The trait data set is free to use and can be downloaded from ScienceBase: https://www.sciencebase.gov/catalog/item/58af41dee4b01ccd54f9f2ff and https://dx.doi.org/10.5066/F7QV3JN1

Arizona↗

USGS2015

Direct and indirect effects of environmental variability on growth and survivorship of pre-reproductive Joshua trees, Yucca brevifolia Engelm (Agavaceae)

• Premise of study: Accurate demographic information about long-lived plant species is important for understanding responses to large-scale disturbances, including climate change. It is challenging to obtain these data from desert perennial plants because seedling establishment is exceptionally rare, and estimates of survival are lacking for their vulnerable early stages. Desert wildfires, urbanization, and climate change influence the persistence of the long-lived Yucca brevifolia . Quantitative demographic attributes are crucial for understanding how populations will respond to disturbances and where populations will recede or advance under future climate scenarios. • Methods: We measured survival in a cohort of 53 pre-reproductive Y. brevifolia at Yucca Flat, Nevada, USA, for 22 yr and recorded their growth, nurse-plant relationships, and herbivory. • Key results: Herbivory by black-tailed jackrabbits ( Lepus californicus ) caused severe losses of plants during the first and second years (45% and 31%, respectively). Surviving plants experienced <2.5% annual mortality. Survival for the population was 19% over 22 yr. Plants <25 cm in height had lower life expectancy. Average growth rate (± SD) for plants that survived to the last census was 3.12 ± 1.96 cm yr −1 , and growth rates were positively associated with precipitation. Thirty-year-old Y. brevifolia had not yet reproduced. • Conclusions: A rare establishment event for Y. brevifolia during 1983–1984, triggered by above-average summer rainfall, provided a unique opportunity to track early survival and growth. Infrequent but acute episodes of herbivory during drought influenced demography for decades. Variability in survival among young Y. brevifolia indicates that size-dependent demographic variables will improve forecasts for this long-lived desert species under predicted regional climate change.

Nevada↗

USGS2011

Predicting phenology by integrating ecology, evolution and climate science

Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology – the timing of life‐history events. Phenology has well‐demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species’ reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.

Global Change Biology↗

USGS2007

The role of historical fire disturbance in the carbon dynamics of the pan-boreal region: A process-based analysis

[1] Wildfire is a common occurrence in ecosystems of northern high latitudes, and changes in the fire regime of this region have consequences for carbon feedbacks to the climate system. To improve our understanding of how wildfire influences carbon dynamics of this region, we used the process-based Terrestrial Ecosystem Model to simulate fire emissions and changes in carbon storage north of 45°N from the start of spatially explicit historically recorded fire records in the twentieth century through 2002, and evaluated the role of fire in the carbon dynamics of the region within the context of ecosystem responses to changes in atmospheric CO 2 concentration and climate. Our analysis indicates that fire plays an important role in interannual and decadal scale variation of source/sink relationships of northern terrestrial ecosystems and also suggests that atmospheric CO 2 may be important to consider in addition to changes in climate and fire disturbance. There are substantial uncertainties in the effects of fire on carbon storage in our simulations. These uncertainties are associated with sparse fire data for northern Eurasia, uncertainty in estimating carbon consumption, and difficulty in verifying assumptions about the representation of fires that occurred prior to the start of the historical fire record. To improve the ability to better predict how fire will influence carbon storage of this region in the future, new analyses of the retrospective role of fire in the carbon dynamics of northern high latitudes should address these uncertainties.

Journal of Geophysical Research G: Biogeosciences↗

USGS2020

Legacy effects of hydrologic alteration in playa wetland responses to droughts

Wetland conservation increasingly must account for climate change and legacies of previous land-use practices. Playa wetlands provide critical wildlife habitat, but may be impacted by intensifying droughts and previous hydrologic modifications. To inform playa restoration planning, we asked: (1) what are the trends in playa inundation? (2) what are the factors influencing inundation? (3) how is playa inundation affected by increasingly severe drought? (4) do certain playas provide hydrologic refugia during droughts, and (5) if so, how are refugia patterns related to historical modifications? Using remotely sensed surface-water data, we evaluated a 30-year time series (1985–2015) of inundation for 153 playas of the Great Basin, USA. Inundation likelihood and duration increased with wetter weather conditions and were greater in modified playas. Inundation probability was projected to decrease from 22% under average conditions to 11% under extreme drought, with respective annual inundation decreasing from 1.7 to 0.9 months. Only 4% of playas were inundated for at least 2 months in each of the 5 driest years, suggesting their potential as drought refugia. Refugial playas were larger and more likely to have been modified, possibly because previous land managers selected refugial playas for modification. These inundation patterns can inform efforts to restore wetland functions and to conserve playa habitats as climate conditions change.

Nevada, Oregon↗

USGS2017

Climate-mediated competition in a high-elevation salamander community

The distribution of the federally endangered Shenandoah Salamander ( Plethodon shenandoah ) is presumed to be limited by competition with the Red-backed Salamander ( Plethodon cinereus ). In particular, the current distribution of P. shenandoah is understood to be restricted to warmer and drier habitats because of interspecific interactions. These habitats may be particularly sensitive to climate change, though the influence of competition may also be affected by temperature and relative humidity. We investigated the response of P. shenandoah to competition with P. cinereus under four climate scenarios in 3-dimensional mesocosms. The results suggest that, although climate change may alleviate competitive pressure from P. cinereus , warmer temperatures may also significantly influence the persistence of the species across its known range.

Journal of Herpetology↗