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At least 1,171 records · Page 65Linked to original sources

USGS2018

Combining InSAR and GPS to determine transient movement and thickness of a seasonally active low-gradient translational landslide

The combined application of continuous Global Positioning System data (high temporal resolution) with spaceborne interferometric synthetic aperture radar data (high spatial resolution) can reveal much more about the complexity of large landslide movement than is possible with geodetic measurements tied to only a few specific measurement sites. This approach is applied to an ~4 km 2 reactivated translational landslide in the Columbia River Gorge (Washington State), which moves mainly during the winter rainy season. Results reveal the complex three-dimensional shape of the landslide mass, how onset of sliding relates to cumulative rainfall, how surface velocity during sliding varies with location on the topographically complex landslide surface, and how the ground surface subsides slightly in weeks prior to downslope sliding.

Geophysical Research Letters↗

USGS2016

Surficial geological tools in fluvial geomorphology: Chapter 2

Increasingly, environmental scientists are being asked to develop an understanding of how rivers and streams have been altered by environmental stresses, whether rivers are subject to physical or chemical hazards, how they can be restored, and how they will respond to future environmental change. These questions present substantive challenges to the discipline of fluvial geomorphology, especially since decades of geomorphologic research have demonstrated the general complexity of fluvial systems. It follows from the concept of complex response that synoptic and short-term historical views of rivers will often give misleading understanding of future behavior. Nevertheless, broadly trained geomorphologists can address questions involving complex natural systems by drawing from a tool box that commonly includes the principles and methods of geology, hydrology, hydraulics, engineering, and ecology.

Book chapter↗

USGS2019

Spatially explicit network analysis reveals multi-species annual cycle movement patterns of sea ducks

Conservation of long-distance migratory species poses unique challenges. Migratory connectivity—that is, the extent to which groupings of individuals at breeding sites are maintained in wintering areas—is frequently used to evaluate population structure and assess use of key habitat areas. However, for species with complex or variable annual-cycle movements, this traditional bimodal framework of migratory connectivity may be overly simplistic. Like many other waterfowl, sea ducks often travel to specific pre- and post-breeding sites outside their nesting and wintering areas to prepare for migration and, in some cases, molt their flight feathers. These additional molt migrations may play a key role in population structure, but are not included in traditional models of migratory connectivity. Network analysis, which applies graph theory to assess landscape connectivity, offers a powerful tool for quantitatively assessing the contributions of different sites used throughout the annual cycle to complex spatial networks. We collected satellite telemetry data on annual cycle movements of over 500 individual sea ducks of five species from throughout eastern North America and the Great Lakes. From these data, we constructed a multi-species network model of migratory patterns and site use over the course of the breeding, molting, wintering, and migration periods. Our results highlight inter- and intra-specific differences in the patterns and complexity of annual-cycle movement patterns, including the central importance of staging and molting sites in James Bay and the St. Lawrence River to multi-species habitat connectivity. We also discuss potential applications of network migration models to conservation prioritization, identification of population units, and integrating different data streams.

Ecological Applications↗

USGS2023

A big data–model integration approach for predicting epizootics and population recovery in a keystone species

Infectious diseases pose a significant threat to global health and biodiversity. Yet, predicting the spatiotemporal dynamics of wildlife epizootics remains challenging. Disease outbreaks result from complex nonlinear interactions among a large collection of variables that rarely adhere to the assumptions of parametric regression modeling. We adopted a nonparametric machine learning approach to model wildlife epizootics and population recovery, using the disease system of colonial black-tailed prairie dogs (BTPD, Cynomys ludovicianus ) and sylvatic plague as an example. We synthesized colony data between 2001 and 2020 from eight USDA Forest Service National Grasslands across the range of BTPDs in central North America. We then modeled extinctions due to plague and colony recovery of BTPDs in relation to complex interactions among climate, topoedaphic variables, colony characteristics, and disease history. Extinctions due to plague occurred more frequently when BTPD colonies were spatially clustered, in closer proximity to colonies decimated by plague during the previous year, following cooler than average temperatures the previous summer, and when wetter winter/springs were preceded by drier summers/falls. Rigorous cross-validations and spatial predictions indicated that our final models predicted plague outbreaks and colony recovery in BTPD with high accuracy (e.g., AUC generally >0.80). Thus, these spatially explicit models can reliably predict the spatial and temporal dynamics of wildlife epizootics and subsequent population recovery in a highly complex host–pathogen system. Our models can be used to support strategic management planning (e.g., plague mitigation) to optimize benefits of this keystone species to associated wildlife communities and ecosystem functioning. This optimization can reduce conflicts among different landowners and resource managers, as well as economic losses to the ranching industry. More broadly, our big data–model integration approach provides a general framework for spatially explicit forecasting of disease-induced population fluctuations for use in natural resource management decision-making.

Arizona, Colorado, Kansas, Montana, Nebraska, New ↗

USGS2018

A method to detect discontinuities in census data

The distribution of pattern across scales has predictive power in the analysis of complex systems. Discontinuity approaches remain a fruitful avenue of research in the quest for quantitative measures of resilience because discontinuity analysis provides an objective means of identifying scales in complex systems and facilitates delineation of hierarchical patterns in processes, structure, and resources. However, current discontinuity methods have been considered too subjective, too complicated and opaque, or have become computationally obsolete; given the ubiquity of discontinuities in ecological and other complex systems, a simple and transparent method for detection is needed. In this study, we present a method to detect discontinuities in census data based on resampling of a neutral model and provide the R code used to run the analyses. This method has the potential for advancing basic and applied ecological research.

Ecology and Evolution↗

USGS2016

The statistical power to detect cross-scale interactions at macroscales

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

Ecosphere↗

USGS2017

The value of information for woodland management: Updating a state–transition model

Value of information (VOI) analyses reveal the expected benefit of reducing uncertainty to a decision maker. Most ecological VOI analyses have focused on population models rarely addressing more complex community models. We performed a VOI analysis for a complex state–transition model of Box-Ironbark Forest and Woodland management. With three management alternatives (limited harvest/firewood removal (HF), ecological thinning (ET), and no management), managing the system optimally (for 150 yr) with the original information would, on average, increase the amount of forest in a desirable state from 19% to 35% (a 16-percentage point increase). Resolving all uncertainty would, on average, increase the final percentage to 42% (a 19-percentage point increase). However, only resolving the uncertainty for a single parameter was worth almost two-thirds the value of resolving all uncertainty. We found the VOI to depend on the number of management options, increasing as the management flexibility increased. Our analyses show it is more cost-effective to monitor low-density regrowth forest than other states and more cost-effective to experiment with the no-management alternative than the other management alternatives. Importantly, the most cost-effective strategies did not include either the most desired forest states or the least understood management strategy, ET. This implies that managers cannot just rely on intuition to tell them where the most VOI will lie, as critical uncertainties in a complex system are sometimes cryptic.

Victoria↗

USGS2020

Is your ad hoc model selection strategy affecting your multimodel inference?

(Yackulic) 1. Ecologists routinely fit complex models with multiple parameters of interest, where hundreds or more competing models are plausible. To limit the number of fitted models, ecologists often define a model selection strategy composed of a series of stages in which certain features of a model are compared while other features are held constant. Defining these multi-stage strategies requires making a series of decisions, which may potentially impact inferences, but have not been critically evaluated. 2. We begin by identifying key features of strategies, introducing descriptive terms when they did not already exist in the literature. Strategies differ in how they define and order model building stages. Sequential-by-sub-model strategies focus on one sub-model (parameter) at a time with modeling of subsequent sub-models dependent on the selected model structures from the previous stages. Secondary candidate set strategies model sub-models independently and combine the top set of models from each sub-model for selection in a final stage. Build-up approaches define stages across sub-models and increase in complexity at each stage. Strategies also differ in how the top set of models is selected in each stage and whether they use null or more complex model structures for non-target sub-models. 3. We tested the performance of different model selection strategies using four datasets and three model types. For each dataset, we determined the “true” distribution of AIC weights by fitting all plausible models. Then, we calculated the number of models that would have been fitted and the portion of “true” AIC weight we recovered under different model selection strategies. 4. Sequential-by-sub-model strategies often performed poorly. Build-up or secondary candidate sets were more reliable, provided all models within 5 AIC of the top model were carried forward to subsequent stages. The structure of non-target sub-models was less important. 5. Multi-stage approaches cannot compensate for a lack of critical thought in selecting covariates and building models to represent competing a priori hypotheses. However, even when competing hypotheses for different sub-models are limited, thousands or more models may be possible so strategies to explore candidate model space reliably and efficiently will be necessary.

Ecosphere↗

USGS2005

Development of partial rock veneers by root throw in a subalpine setting

Rock veneers stabilize hillslope surfaces, occur especially in areas of immature soil, and form through a variety of process sets that includes root throw. Near Westcliffe, Colorado, USA, data were collected from a 20 ?? 500 m transect on the east slope of the Sangre de Cristo Mountains. Ages of pit/mound complexes with rock fragments exposed at the surface by root throw ranged from recent (freshly toppled tree) to unknown (complete tree decay). Calculations based on dimensions of the pit/mound complexes, estimated time of free topppling, sizes of exposed rock fragments, and percentage rock covers at pit/mound complexes, as well as within the transect area, indicate that recent rates of root throw have resulted in only partial rock veneering since late Pleistocene deglaciation. Weathering of rock fragments prevent development of an extensive rock veneer and causes a balance, achieved within an estimated 700 years, between the rates of rock-fragment exposure by root throw and clast disintegration by chemical reduction. The estimated rate of rock-fragment reduction accounts for part of the fluvial sediment yields observed for forested subalpine areas of western North America. Copyright ?? 2005 John Wiley & Sons, Ltd.

Earth Surface Processes and Landforms↗

USGS2021

Relative effectiveness of D-Frame dip nets, quatrefoil light traps, and towed ichthyoplankton nets for larval Muskellunge

Muskellunge Esox masquinongy are large, predatory game fish whose association with shallow, complex habitats is well documented, particularly during early life stages. Despite this association, relatively little guidance exists regarding effective sampling of Muskellunge larvae and previous efforts to sample larval Muskellunge have been met with limited success. Therefore, our objective was to determine the relative effectiveness of three sampling gears for capturing naturally produced Muskellunge larvae. Larvae were sampled during 2019 and 2020 at known Muskellunge spawning locations in Snipe Lake, Wisconsin, with D-frame dip nets (1,000-µm mesh), quatrefoil light traps, and towed ichthyoplankton nets (1,000-µm mesh). Sixty larval Muskellunge were captured across all gears, and catches in D-frame dip nets comprised nearly 87% (52 of 60) of the total catch. Furthermore, D-frame dip nets captured the broadest size range of larval Muskellunge (TL range = 14–33 mm). Greater effectiveness of D-frame dip nets in comparison with other gears is likely related to their ability to be used in and around structurally complex habitats without fouling or clogging. Our results suggest that D-frame dip nets should be considered as a cost- and time-effective tool for targeting larval Muskellunge in complex habitats.

Wisconsin↗

USGS2024

Wood you believe it? Experimental addition of nonnative wood enhances instream habitat for native dryland fishes

Flow alteration and riparian vegetation encroachment are causing habitat simplification with severe consequences for native fishes. To assess the effectiveness of enhancing simplified habitat in a large dryland river, we experimentally added invasive wood at 19 paired treatment and reference (no wood added) subreaches (50–100 m) within the main channel of the San Juan River. Using a before-after-control-impact design, we sampled fishes and macroinvertebrates, and quantified habitat complexity. After wood addition, total native fish densities were 2.2× higher in treatments compared with references, whereas total nonnative fish densities exhibited no response. Macroinvertebrate densities were 6.8× higher, and habitat complexity increased in treatments. Counts of geomorphic features in treatments increased from 1 to a maximum of 11 following wood addition, while the number of features in references remained unchanged. Wood addition has potential to instigate natural riverine processes, ultimately enhancing native fish habitat by increasing macroinvertebrate densities and habitat complexity in dryland rivers. Water overallocation and increasing aridity will continue to challenge efforts to improve habitat conditions with environmental flows alone, and managers might consider integrating non-flow alternatives like addition of abundant, invasive wood to reduce habitat simplification.

New Mexico, Utah↗

USGS2024

Effects of 2D hydrodynamic model resolution on habitat estimates for rearing Coho Salmon in contrasting channel forms

Estimating the impacts of water allocation decisions on fish populations and habitat availability is an important part of environmental flow assessments, especially in locations where water resources are limited. Two-dimensional hydrodynamic models (2DHMs) are commonly coupled with biological models to estimate fish habitat quality, area, and capacity across a range of proposed streamflows. Increasingly, resource managers are relying on landscape-scale model domains with coarse model resolutions to maintain feasible computational loads, but this may affect habitat estimates if the mesh element size of the model exceeds the spatial scale relevant to the organism. We investigated how coarsening the resolution of a 2DHM influences the area and spatial distribution of estimated Coho Salmon ( Oncorhynchus kisutch ) fry habitats. We used an interpolation scheme that upscaled mesh elements from a high-resolution (0.25 m 2 ) 2DHM to quantify and visualize the effects of 2DHM resolution on estimates of Coho Salmon fry habitat for two contrasting channel morphologies and across a broad range of streamflows. Estimates of Coho Salmon fry habitat at increasingly coarser resolutions led to 20%–50% reductions in weighted usable habitat area (WUA) across several streamflow scenarios for a complex channel type, but did not impact estimates in a confined, flume-like channel. Additionally, flow-to-habitat area relationships were not congruent at a given streamflow when resolution coarsened. Along with almost 500% more high-quality habitat area estimated in the complex channel type over the confined, discrepancies in habitat area increased with higher flows in areas defined as optimal for rearing Coho Salmon fry. Considering that complex channel types contain critical habitat for Coho Salmon fry, this study suggests coarse 2DHM resolutions may exclude important wetted edge and off-channel habitats from environmental flow assessments.

California↗

USGS2025

Monitoring lightning and electrification in volcanic plumes

Detection of the electrical discharges and, more fundamentally, the electrification from volcanic plumes is an emerging capability for volcano monitoring. In addition to being able to detect an explosive eruption, such measurements also provide insight into volcanic processes. Volcanic lightning monitoring can be achieved through varying levels of complexity. At the lowest complexity, an observatory can use low-cost global lightning data sets for eruption detection and characterization, while at the highest complexity local lightning sensors can be installed to improve the level of observational detail and response times. This chapter provides background about volcanic lightning and plume electrification, information concerning the relevant instrumentation to detect lightning and electrified plumes, examples of how lightning can be used to understand eruptive processes, and a guide to implementing volcanic lightning detection into a monitoring scheme.

Book chapter↗

USGS2013

Ecosystem services: developing sustainable management paradigms based on wetland functions and processes

In the late nineteenth century and twentieth century, there was considerable interest and activity to develop the United States for agricultural, mining, and many other purposes to improve the quality of human life standards and prosperity. Most of the work to support this development was focused along disciplinary lines with little attention focused on ecosystem service trade-offs or synergisms, especially those that transcended boundaries of scientific disciplines and specific interest groups. Concurrently, human population size has increased substantially and its use of ecosystem services has increased more than five-fold over just the past century. Consequently, the contemporary landscape has been highly modified for human use, leaving behind a fragmented landscape where basic ecosystem functions and processes have been broadly altered. Over this period, climate change also interacted with other anthropogenic effects, resulting in modern environmental problems having a complexity that is without historical precedent. The challenge before the scientific community is to develop new science paradigms that integrate relevant scientific disciplines to properly frame and evaluate modern environmental problems in a systems-type approach to better inform the decision-making process. Wetland science is a relatively new discipline that grew out of the conservation movement of the early twentieth century. In the United States, most of the conservation attention in the earlier days was on wildlife, but a growing human awareness of the importance of the environment led to the passage of the National Environmental Policy Act in 1969. Concurrently, there was a broadening interest in conservation science, and the scientific study of wetlands gradually gained acceptance as a scientific discipline. Pioneering wetland scientists became formally organized when they formed The Society of Wetland Scientists in 1980 and established a publication outlet to share wetland research findings. In comparison to older and more traditional scientific disciplines, the wetland sciences may be better equipped to tackle today’s complex problems. Since its emergence as a scientific discipline, the study of wetlands has frequently required interdisciplinary and integrated approaches. This interdisciplinary/integrated approach is largely the result of the fact that wetlands cannot be studied in isolation of upland areas that contribute surface and subsurface water, solutes, sediments, and nutrients into wetland basins. However, challenges still remain in thoroughly integrating the wetland sciences with scientific disciplines involved in upland studies, especially those involved with agriculture, development, and other land-conversion activities that influence wetland hydrology, chemistry, and sedimentation. One way to facilitate this integration is to develop an understanding of how human activities affect wetland ecosystem services, especially the trade-offs and synergisms that occur when land-use changes are made. Used in this context, an understanding of the real costs of managing for a particular ecosystem service or groups of services can be determined and quantified in terms of reduced delivery of other services and in overall sustainability of the wetland and the landscapes that support them. In this chapter, we discuss some of the more salient aspects of a few common wetland types to give the reader some background on the diversity of functions that wetlands perform and the specific ecosystem services they provide to society. Wetlands are among the most complex ecosystems on the planet, and it is often difficult to communicate to a diverse public all of the positive services wetlands provide to mankind. Our goal is to help the reader develop an understanding that management options can be approached as societal choices where decisions can be made within a spatial and temporal context to identify trade-offs, synergies, and effects on long-term sustainability of wetland ecosystems. This will be especially relevant as we move into alternate climate futures where our portfolio of management options for mitigating damage to ecosystem function or detrimental cascading effects must be diverse and effective.

Book chapter↗

USGS1994

Distribution and status of submerged vegetation in estuaries of the upper Texas coast

Composition and biomass of beds of submerged aquatic vegetation (SAV) in estuaries along the upper Texas coast were examined from bottom core and rake samples taken along 72 line transects during July–August 1987. Substrate composition, salinity, water depth, and water clarity were also measured at each sample station. Halodule wrightii was the dominant species of SAV meadows (69% occurrence), followed by Ruppia maritima (36%). Najas guadalupensis and Vallisneria americana were only found in the shallow (<60 cm), oligohaline (<10 ppt) waters of Trinity Bay. Halophila engelmannii and Thalassia testudinum were only found in the deeper (35–110 cm) euhaline waters (30–40 ppt) of Christmas and Matagorda Bays. H. wrightii and R. maritima occurred across the greatest depth and salinity spectra, with R. maritima more prominent in shallower (<90 cm) mixohaline waters (10–30 ppt) and H. wrightii more prominent in euhaline waters (30–40 ppt). Beds of SAV were more extensive and had greater biomass along south shorelines compared to north shorelines (P<0.045), and depth to which vegetation grew was positively correlated with water clarity (r=0.927, P<0.001). The correlations of water depth, salinity, and water clarity with variation in SAV species composition and distribution suggest that abiotic tolerances documented by previous experimental studies are major factors influencing field distributions. Comparisons with similar field data from the early 1970s corroborate the reported decrease in SAV in the Galveston Bay complex and suggest a slight increase in the Matagorda Bay complex. Decline of SAV in the Galveston Bay complex coincided with major shorefront development and a decline in numbers of wintering redhead ducks Aythya americana . Protection of shorelines of upper coast estuaries is vital to maintaining SAV resources and the dependent fauna. Where possible, barrier island preserves should be established adjacent to beds of-SAV and development restrictions implemented to reduce impacts.

Texas↗

USGS2005

Residues of toxaphene in insectivorous birds ( Petrochelidon spp.) from the Rio Grande, Texas

Although it has been documented that wildlife in the Rio Grande Valley (RGV) contain increased concentrations of organochlorine (OC) contaminants, particularly DDE, little has been published on residues of toxaphene throughout this major North American watershed. In this study, 28 liver composites from adult swallows ( Petrochelidon spp.) collected along the Rio Grande from 1999 through 2000 were analyzed for toxaphene residues using congener-specific gas chromatography–electron-capture negative ionization–mass spectrometry. Estimated total toxaphene concentrations ranged from 12 to 260 ng/g wet wt and were highest in samples from the lower RGV near Llano Grande Lake in Hidalgo and Cameron counties (Texas). Toxaphene congener profiles were relatively invariant throughout the watershed and were dominated by 2,2,5-endo,6-exo,8,8,9,10-octachlorobornane (P-42a or B8-806) with lesser amounts of several other Cl 7 -Cl 9 compounds, many of which remain unidentified. Petrochelidon spp. liver profiles appear to be intermediate in complexity between those in invertebrates and fish (more complex) and mammals (less complex) and differs somewhat from those reported for other avian species. In addition to other legacy OC contaminants, toxaphene residues were most concentrated in the lower RGV and accumulated at up to hundreds of parts per billion in these insect-eating birds, underscoring their utility as avian bioindicators of persistent organic pollutants.

Archives of Environmental Contamination and Toxico↗

USGS2004

LIDAR optical rugosity of coral reefs in Biscayne National Park, Florida

The NASA Experimental Advanced Airborne Research Lidar (EAARL), a temporal waveform-resolving, airborne, green wavelength LIDAR (light detection and ranging), is designed to measure the submeter-scale topography of shallow reef substrates. Topographic variability is a prime component of habitat complexity, an ecological factor that both expresses and controls the abundance and distribution of many reef organisms. Following the acquisition of EAARL coverage over both mid-platform patch reefs and shelf-margin bank reefs within Biscayne National Park in August 2002, EAARL-based optical indices of topographic variability were evaluated at 15 patch reef and bank reef sites. Several sites were selected to match reefs previously evaluated in situ along underwater video and belt transects. The analysis used large populations of submarine topographic transects derived from the examination of closely spaced laser spot reflections along LIDAR raster scans. At all 15 sites, each LIDAR transect was evaluated separately to determine optical rugosity (Rotran), and the average elevation difference between adjacent points (Av(??E ap)). Further, the whole-site mean and maximum values of Ro tran and Av(??Eap) for the entire population of transects at each analysis site, along with their standard deviations, were calculated. This study revealed that the greater habitat complexity of inshore patch reefs versus outer bank reefs results in relative differences in topographic complexity that can be discerned in the laser returns. Accordingly, LIDAR sensing of optical rugosity is proposed as a complementary new technique for the rapid assessment of shallow coral reefs. ?? Springer-Verlag 2004.

Coral Reefs↗

USGS2008

Patch-reef morphology as a proxy for Holocene sea-level variability, Northern Florida Keys, USA

A portion of the northern Florida Keys reef tract was mapped with the NASA Experimental Advanced Airborne Research Lidar (EAARL) and the morphology of patch reefs was related to variations in Holocene sea level. Following creation of a lidar digital elevation model (DEM), geospatial analyses delineated morphologic attributes of 1,034 patch reefs (reef depth, basal area, height, volume, and topographic complexity). Morphometric analysis revealed two morphologically different populations of patch reefs associated with two distinct depth intervals above and below a water depth of 7.7 m. Compared to shallow reefs, the deep reefs were smaller in area and volume and showed no trend in topographic complexity relative to water depth. Shallow reefs were more variable in area and volume and became flatter and less topographically complex with decreasing water depth. The knoll-like morphology of deep reefs was interpreted as consistent with steady and relatively rapidly rising early Holocene sea level that restricted the lateral growth of reefs. The morphology of shallow 'pancake-shaped' reefs at the highest platform elevations was interpreted as consistent with fluctuating sea level during the late Holocene. Although the ultimate cause for the morphometric depth trends remains open to interpretation, these interpretations are compatible with a recent eustatic sea-level curve that hindcasts fluctuating late Holocene sea level. Thus it is suggested that the morphologic differences represent two stages of reef accretion that occurred during different sea-level conditions. ?? 2008 Springer-Verlag.

Coral Reefs↗