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At least 685 records · Page 38Linked to original sources
USGS2022

Framework for assessing and mitigating the impacts of offshore wind energy development on marine birds

Offshore wind energy development (OWED) is rapidly expanding globally and has the potential to contribute significantly to renewable energy portfolios. However, development of infrastructure in the marine environment presents risks to wildlife. Marine birds in particular have life history traits that amplify population impacts from displacement and collision with offshore wind infrastructure. Here, we present a broadly applicable framework to assess and mitigate the impacts of OWED on marine birds. We outline existing techniques to quantify impact via monitoring and modeling (e.g., collision risk models, population viability analysis), and present a robust mitigation framework to avoid, minimize, or compensate for OWED impacts. Our framework addresses impacts within the context of multiple stressors across multiple wind energy developments. We also present technological and methodological approaches that can improve impact estimation and mitigation. We highlight compensatory mitigation as a tool that can be incorporated into regulatory frameworks to mitigate impacts that cannot be avoided or minimized via siting decisions or alterations to OWED infrastructure or operation. Our framework is intended as a globally-relevant approach for assessing and mitigating OWED impacts on marine birds that may be adapted to existing regulatory frameworks in regions with existing or planned OWED.

Biological Conservation↗
USGS2024

Revisiting the physical processes controlling the tropical atmospheric circulation changes during the Mid-Piacenzian Warm Period

The Mid-Piacenzian Warm Period (MPWP; 3.0–3.3 Ma), a warm geological period about three million years ago, has been deemed as a good past analog for understanding the current and future climate change. Based on 12 climate model outputs from Pliocene Model Intercomparison Project Phase 2 (PlioMIP2), we investigate tropical atmospheric circulation (TAC) changes under the warm MPWP and associated underlying mechanisms by diagnosing both atmospheric static stability and diabatic processes. Our findings underscore the advantage of analyzing atmospheric diabatic processes in elucidating seasonal variations of TAC compared to static stability assessments. Specifically, by diagnosing alterations in diabatic processes, we achieve a quantitative understanding and explanation the following TAC changes (incl. Strength and edge) during the MPWP: the weakened (annual, DJF, JJA) Northern Hemisphere and (DJF) Southern Hemisphere Hadley circulation (HC), reduced (annual, DJF) Pacific Walker circulation (PWC) and enhanced (annual, JJA) Southern Hemisphere HC and (JJA) PWC, and westward shifted (annual, DJF, JJA) PWC. We further addressed that the increasing bulk subtropical static stability and/or decreasing vertical shear of subtropical zonal wind - two crucial control factors for changes in subtropical baroclinicity - may promote HC widening, and vice versa. Consequently, our study of spatial diabatic heating and cooling, corresponding to upward and downward motions within the TAC, respectively, provides a new perspective for understanding the processes controlling seasonal TAC changes in response to surface warming.

Quaternary International↗
USGS2017

Multi-temporal LiDAR and Landsat quantification of fire-induced changes to forest structure

Measuring post-fire effects at landscape scales is critical to an ecological understanding of wildfire effects. Predominantly this is accomplished with either multi-spectral remote sensing data or through ground-based field sampling plots. While these methods are important, field data is usually limited to opportunistic post-fire observations, and spectral data often lacks validation with specific variables of change. Additional uncertainty remains regarding how best to account for environmental variables influencing fire effects (e.g., weather) for which observational data cannot easily be acquired, and whether pre-fire agents of change such as bark beetle and timber harvest impact model accuracy. This study quantifies wildfire effects by correlating changes in forest structure derived from multi-temporal Light Detection and Ranging (LiDAR) acquisitions to multi-temporal spectral changes captured by the Landsat Thematic Mapper and Operational Land Imager for the 2012 Pole Creek Fire in central Oregon. Spatial regression modeling was assessed as a methodology to account for spatial autocorrelation, and model consistency was quantified across areas impacted by pre-fire mountain pine beetle and timber harvest. The strongest relationship (pseudo-r 2 = 0.86, p < 0.0001) was observed between the ratio of shortwave infrared and near infrared reflectance (d74) and LiDAR-derived estimate of canopy cover change. Relationships between percentage of LiDAR returns in forest strata and spectral indices generally increased in strength with strata height. Structural measurements made closer to the ground were not well correlated. The spatial regression approach improved all relationships, demonstrating its utility, but model performance declined across pre-fire agents of change, suggesting that such studies should stratify by pre-fire forest condition. This study establishes that spectral indices such as d74 and dNBR are most sensitive to wildfire-caused structural changes such as reduction in canopy cover and perform best when that structure has not been reduced pre-fire.

Oregon↗
USGS2025

A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation

Accurate mapping of headwater streams and their flow status has important implications for understanding and managing water resources and land uses. However, accurate information is rare, especially in rugged, forested terrain. We developed a streamflow permanence classification model for forested lands in western Oregon using the latest light detection and ranging-derived hydrography published in the National Hydrography Dataset. Models were trained using 2,518 flow/no flow field observations collected in late summer 2019–2021 across headwaters of 129 sub-watersheds. The final model, the Western Oregon WeT DRy model, used Random Forest and 13 environmental covariates for classifying every 5-m stream sub-reach across 426 sub-watersheds. The most important covariates were annual precipitation and drainage area. Model output included probabilities of late summer surface flow presence and were subsequently categorized into three streamflow permanence classes—Wet, Dry, and Ambiguous. Ambiguous denoted model probabilities and associated prediction intervals that extended over the 50% classification threshold between wet and dry. Model accuracy was 0.83 for sub-watersheds that contained training data and decreased to 0.67 for sub-watersheds that did not have observations of late summer surface flow. The model identified where predictions extrapolated beyond the domain characterized by the training data. The combination of spatially continuous estimates of late summer streamflow status along with uncertainty and extrapolation estimates provide critical information for strategic project planning and designing additional field data collection.

Oregon↗
USGS2012

Assessing confidence in Pliocene sea surface temperatures to evaluate predictive models

In light of mounting empirical evidence that planetary warming is well underway, the climate research community looks to palaeoclimate research for a ground-truthing measure with which to test the accuracy of future climate simulations. Model experiments that attempt to simulate climates of the past serve to identify both similarities and differences between two climate states and, when compared with simulations run by other models and with geological data, to identify model-specific biases. Uncertainties associated with both the data and the models must be considered in such an exercise. The most recent period of sustained global warmth similar to what is projected for the near future occurred about 3.3–3.0 million years ago, during the Pliocene epoch. Here, we present Pliocene sea surface temperature data, newly characterized in terms of level of confidence, along with initial experimental results from four climate models. We conclude that, in terms of sea surface temperature, models are in good agreement with estimates of Pliocene sea surface temperature in most regions except the North Atlantic. Our analysis indicates that the discrepancy between the Pliocene proxy data and model simulations in the mid-latitudes of the North Atlantic, where models underestimate warming shown by our highest-confidence data, may provide a new perspective and insight into the predictive abilities of these models in simulating a past warm interval in Earth history. This is important because the Pliocene has a number of parallels to present predictions of late twenty-first century climate.

Nature Climate Change↗
USGS2024

Decomposition of physical processes controlling EASM precipitation changes during the mid-Piacenzian: New insights into data–model integration

The mid-Piacenzian warm period (MPWP, ~3.264–3.025 Ma) has gained widespread interest due to its partial analogy with future climate. However, quantitative data–model comparison of East Asian Summer Monsoon (EASM) precipitation during the MPWP is relatively rare, especially due to problems in decoding the imprint of physical processes to climate signals in the records. In this study, pollen-based precipitation records are reconstructed and compared to the multi-model ensemble mean of the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2). We find spatially consistent precipitation increase in most simulations but a spatially divergent change in MPWP records. We reconcile proxy data and simulation by decomposing physical processes that control precipitation. Our results 1) reveal thermodynamic control of an overall enhancement of EASM precipitation and 2) highlight a distinct control of thermodynamic and dynamical processes on increases of tropical and subtropical EASM precipitation, reflecting the two pathways of water vapor supply that enhance EASM precipitation, respectively.

npj Climate and Atmospheric Science↗
USGS2016

Economic consequence analysis of the Arkstorm scenario

The business interruption (BI) impacts of ARkStorm, a severe winter storm scenario developed by the U.S. Geological Survey and partners, is estimated. BI stems from losses of building function, productivity of agricultural land, and lifeline services. A dynamic computable general equilibrium model of the California economy is developed to perform this economic consequence analysis. Economic resilience in the form of input and import substitution is inherent in the model’s equilibrium solution, and the model parameterization is adjusted to reflect other forms of resilience such as production recapture. Varying assumptions about the timing and source of funds for reconstruction results in a range of recovery paths. Five years after the storm, flood-induced building damage is the overwhelming source of gross domestic product (GDP) losses, timely and partially externally funded reconstruction mitigates impacts by approximately 50%, and the economy is not guaranteed to return to its baseline GDP trajectory. The methodology serves as a template for assessing the macroeconomic consequences of disasters and the influence of resilience in reducing BI losses.

National Hazards Review↗
USGS2016

Economic impacts of a California tsunami

The economic consequences of a tsunami scenario for Southern California are estimated using computable general equilibrium analysis. The economy is modeled as a set of interconnected supply chains interacting through markets but with explicit constraints stemming from property damage and business downtime. Economic impacts are measured by the reduction of Gross Domestic Product for Southern California, Rest of California, and U.S. economies. For California, total economic impacts represent the general equilibrium (essentially quantity and price multiplier) effects of lost production in industries upstream and downstream in the supply-chain of sectors that are directly impacted by port cargo disruptions at Port of Los Angeles and Port of Long Beach (POLA/POLB), property damage along the coast, and evacuation of potentially inundated areas. These impacts are estimated to be $2.2 billion from port disruptions, $0.9 billion from property damages, and $2.8 billion from evacuations. Various economic-resilience tactics can potentially reduce the direct and total impacts by 80–85%.

California↗
USGS2022

Economic consequences of the HayWired earthquake scenario

This study evaluates the economic impacts of a M w 7.0 Hayward fault scenario earthquake on the greater San Francisco Bay Region’s economy and the California economy as a whole using a detailed multiregional, static computable general equilibrium model. Economic impacts in terms of Gross Regional Product (GRP) losses caused by both capital stock (building and content) damages and water and electricity utilities, and telecommunications-service disruptions are estimated. The results indicate that the total losses are primarily caused by capital stock damages. In the 6 months following the earthquake, total GRP losses are estimated to be $44.2 billion (4.2 percent of California’s projected baseline GRP over the period), but this result could be reduced by about 43 percent to $25.3 billion after factoring in microeconomic resilience tactics. The GRP losses associated with lifeline service disruptions are estimated to be $1.4 billion, which can be reduced by over 85 percent when resilience tactics are implemented. The most effective tactics are the ability to make up lost production by people working overtime or extra shifts (production recapture), making greater use of processes that do not need disrupted goods or services (production isolation), and substituting for disrupted supplies and services (input substitution), though their impact varies across the various causal factors influencing GRP losses.

California↗
USGS2022

Biostratigraphically significant palynofloras from the Paleocene–Eocene boundary of the USA

Pollen and spores were recovered from the Paleocene Fort Union Formation and Paleocene–Eocene Willwood Formation of the Bighorn Basin (BHB), northwestern Wyoming, USA. In many local stratigraphic sections in the BHB, the base of the Eocene has been identified by the characteristic negative carbon isotope excursion (CIE) that marks the beginning of the Paleocene–Eocene Thermal Maximum (PETM). The palynotaxa from outcrop samples were examined using light microscopy (LM) and scanning electron microscopy (SEM). Seven new species are formally described ( Tricolpites vegrandis , Rousea spatium , Striatricolporites astutus , Striatopollis calidarius , Friedrichipollis geminus , Retistephanocolporites modicrassus and Retistephanocolporites pergrandis ). The temporal and geographic distributions of many of these palynotaxa suggest that hotter and more seasonally dry climates facilitated their northward range shifts during the PETM from the tropics or subtropics of the USA. For the temperate palynotaxa, the hotter and seasonally dry conditions resulted in local extirpation. A re-evaluation of the palynostratigraphic schemes established for the Paleocene–Eocene boundary confirms that the first appearance of Platycarya platycaryoides denotes the Paleocene–Eocene boundary in the Rocky Mountains region. A new Striatopollis calidarius Subzone, associated with early Wasatchian (Wa) Wa-0 and Wa-R faunas, is also recognized for CIE body localities in the BHB.

Wyoming↗
USGS2022

How lions move at night when they hunt?

Movement patterns of lions ( Panthera leo ) reveal how they hunt large herbivores in heterogeneous landscapes such as the Kruger National Park in South Africa. Large herbivores are distributed differently on the landscape and therefore have different vulnerabilities as prey for lions. For instance, blue wildebeest ( Connochaetes taurinus ) occupy small grazing lawns at night but are difficult for lions to capture because open areas lack cover for stalking. African buffalo ( Syncerus caffer ) aggregate in large herds but are less available because these herds only intermittently enter the home ranges of individual lion prides. Unlike large herds of wildebeest and buffalo, plains zebra ( Equus quagga ) move widely in small herds while browsing greater kudus ( Tragelaphus strepsiceros ) and giraffes ( Giraffa camelopardalis giraffa ) generally occur in lower densities. We used spatial data derived from GPS collars to investigate several hypotheses regarding the movements of three lion prides in response to their prey. We found that lions were most active and moved longer distances during nighttime than during daytime. Lions remained within their core home ranges on 87% of nights and wandered to the outlying areas of the home ranges every second night. Lions visited grazing lawns, that is, area of short grass, where wildebeest herds resided every second night, and moved toward the direction of buffalo herds within 2 km of vicinity. Lions spent more time near riverbanks that provided dense woody cover at night than expected but concentrated only weakly near sites with surface water where herbivores drank in the dry season. Our study contributes to understanding how lions vary their movements in response to the spatial and temporal heterogeneity in the relative availability and vulnerability of multiple prey species.

Kruger National Park↗
USGS2020

Assessing the exposure of three diving bird species to offshore wind areas on the U.S. Atlantic Outer Continental Shelf using satellite telemetry

Aim The United States Atlantic Outer Continental Shelf (OCS) has considerable offshore wind energy potential. Capturing that resource is part of a broader effort to reduce CO 2 emissions. While few turbines have been constructed in U.S. waters, over a dozen currently planned offshore wind projects have the potential to displace marine birds, potentially leading to effective habitat loss. We focused on three diving birds identified in Europe to be vulnerable to displacement. Our research aimed to determine their potential exposure to areas designated or proposed for offshore wind development along the Atlantic OCS. Methods Satellite tracking technology was used to determine the spatial and temporal use and movement patterns of Surf Scoters ( Melanitta perspicillata ), Red‐throated Loons ( Gavia stellata ) and Northern Gannets ( Morus bassanus ), and calculate their exposure to each offshore wind area. We tagged 236 adults in 2012–2015 on the Atlantic OCS from New Jersey to North Carolina; an additional 147 birds tagged in previous tracking studies were integrated into our analyses. Tracking data were analysed in two‐week intervals using dynamic Brownian bridge movement models to develop composite spatial utilization distributions. For each species, these distributions were then used to calculate the spatio‐temporal exposure to each offshore wind area. Results Surf Scoters and Red‐throated Loons were exposed to offshore wind areas almost exclusively during migration because these species were distributed among coastal and inshore waters during winter months. In contrast, Northern Gannets ranged over a much larger area, reaching farther offshore and south in winter, thus exhibited the greatest exposure to extant offshore wind areas. Conclusions Results of this study provide better understanding of how diving birds use current and potential future offshore wind areas on the Atlantic OCS, and can inform permitting, risk assessment and pre‐ and post‐construction impact assessments of offshore energy infrastructure.

Atlantic Outer Continental Shelf↗
USGS2011

Sensitivity of leaf size and shape to climate: Global patterns and paleoclimatic applications

Paleobotanists have long used models based on leaf size and shape to reconstruct paleoclimate. However, most models incorporate a single variable or use traits that are not physiologically or functionally linked to climate, limiting their predictive power. Further, they often underestimate paleotemperature relative to other proxies. Here we quantify leaf–climate correlations from 92 globally distributed, climatically diverse sites, and explore potential confounding factors. Multiple linear regression models for mean annual temperature (MAT) and mean annual precipitation (MAP) are developed and applied to nine well‐studied fossil floras. We find that leaves in cold climates typically have larger, more numerous teeth, and are more highly dissected. Leaf habit (deciduous vs evergreen), local water availability, and phylogenetic history all affect these relationships. Leaves in wet climates are larger and have fewer, smaller teeth. Our multivariate MAT and MAP models offer moderate improvements in precision over univariate approaches (± 4.0 vs 4.8°C for MAT) and strong improvements in accuracy. For example, our provisional MAT estimates for most North American fossil floras are considerably warmer and in better agreement with independent paleoclimate evidence. Our study demonstrates that the inclusion of additional leaf traits that are functionally linked to climate improves paleoclimate reconstructions. This work also illustrates the need for better understanding of the impact of phylogeny and leaf habit on leaf–climate relationships.

New Phytologist↗
USGS2020

Marine latitudinal diversity gradients, niche conservatism and out of the tropics and Arctic: Climatic sensitivity of small organisms

Aim The latitudinal diversity gradient (LDG) is a consequence of evolutionary and ecological mechanisms acting over long history, and thus is best investigated with organisms that have rich fossil records. However, combined neontological‐palaeontological investigations are mostly limited to large, shelled invertebrates, which keeps our mechanistic understanding of LDGs in its infancy. This paper aims to describe the modern meiobenthic ostracod LDG and to explore the possible controlling factors and the evolutionary mechanisms of this large‐scale biodiversity pattern. Location Present‐day Western North Atlantic. Taxon Ostracoda. Methods We compiled ostracod census data from shallow‐marine environments of the western North Atlantic Ocean. Using these data, we documented the marine LDG with multiple metrics of alpha, beta (nestedness and turnover) and gamma diversity, and we tested whether macroecological patterns could be governed by different environmental factors, including temperature, salinity, dissolved oxygen, pH and primary productivity. We also explored the geologic age distribution of ostracod genera to investigate the evolutionary mechanisms underpinning the LDG. Results Our results show that temperature and climatic niche conservatism are important in setting LDGs of these small, poorly dispersing organisms. We also found evidence for some dispersal‐driven spatial dynamics in the ostracod LDG. Compared to patterns observed in marine bivalves, however, dispersal dynamics were weaker and they were bi‐directional, rather than following the ‘out‐of‐the‐tropics’ model. Main conclusions Our detailed analyses revealed that meiobenthic organisms, which comprise two‐thirds of marine diversity, do not always follow the same rules as larger, better‐studied organisms. Our findings suggest that the understudied majority of biodiversity may be more sensitive to climate than well‐studied, large organisms. This implies that the impacts of ongoing Anthropocene climatic change on marine ecosystems may be much more serious than presently thought.

Journal of Biogeography↗
USGS2003

High plant diversity in Eocene South America: Evidence from Patagonia

Tropical South America has the highest plant diversity of any region today, but this richness is usually characterized as a geologically recent development (Neogene or Pleistocene). From caldera-lake beds exposed at Laguna del Hunco in Patagonia, Argentina, paleolatitude ~47 o S, we report 102 leaf species. Radioisotopic and paleomagnetic analyses indicate that the flora was deposited 52 million years ago, the time of the early Eocene climatic optimum, when tropical plant taxa and warm, equable climates reached middle latitudes of both hemispheres. Adjusted for sample size, observed richness exceeds that of any other Eocene leaf flora, supporting an ancient history of high plant diversity in warm areas of South America.

Science↗
USGS2017

Bacterial sulfur disproportionation constrains timing of neoproterozoic oxygenation

Various geochemical records suggest that atmospheric O 2 increased in the Ediacaran (635–541 Ma), broadly coincident with the emergence and diversification of large animals and increasing marine ecosystem complexity. Furthermore, geochemical proxies indicate that seawater sulfate levels rose at this time too, which has been hypothesized to reflect increased sulfide oxidation in marine sediments caused by sediment mixing of the newly evolved macrofauna. However, the exact timing of oxygenation is not yet understood, and there are claims for significant oxygenation prior to the Ediacaran. Furthermore, recent evidence suggests that physical mixing of sediments did not become important until the late Silurian. Here we report a multiple sulfur isotope record from a ca. 835–630 Ma succession from Svalbard, further supported by data from Proterozoic strata in Canada, Australia, Russia, and the United States, in order to investigate the timing of oxygenation. We present isotopic evidence for onset of globally significant bacterial sulfur disproportionation and reoxidative sulfur cycling following the 635 Ma Marinoan glaciation. Widespread sulfide oxidation helps to explain the observed first-order increase in seawater sulfate concentration from the earliest Ediacaran to the Precambrian-Cambrian boundary by reducing the amount of sulfur buried as pyrite. Expansion of reoxidative sulfur cycling to a global scale also indicates increasing environmental O 2 levels. Thus, our data suggest that increasing atmospheric O 2 levels may have played a role in the emergence of the Ediacaran macrofauna and increasing marine ecosystem complexity.

Geology↗
USGS2023

The long shadow of a major disaster: Modeled dynamic impacts of the hypothetical HayWired earthquake on California’s economy

We develop and apply a dynamic economic simulation model to analyze the multi-regional impacts of, and mechanisms of recovery from, a major disaster, the HayWired scenario — a hypothetical Magnitude 7.0 earthquake affecting California’s San Francisco Bay Area. The model integrates loss pathways: capital stock damage, labor supply shocks due to short-term population displacement and longer-run out-migration from damaged areas, and the exacerbating effects of damage to transportation infrastructure capital, as well as various aspects of static and dynamic economic resilience. With input substitution-based static inherent resilience and dynamic resilience in the form of optimal intertemporal and spatial investment allocation, gross output losses range from 0.5 percent to 6 percent across regions, and welfare losses are 0.4 percent statewide but can be ten times as large in hardest-hit areas. Large-scale reconstruction investment is supported by substantial interregional transfers of resources through intra-state trade. Increased output via firms engaging in the key adaptive resilience tactic of production recapture can alleviate a substantial fraction of losses—but only if upstream and downstream barriers to recovery can be lowered quickly.

California↗