Disturbances elicit both positive and negative effects on organisms; these effects vary in their strength and their timing. Effects of disturbance interval (i.e., the length of time between disturbances) on population growth will depend on both the timing and strength of positive and negative effects of disturbances. Climate change can modify the relative strengths of these positive and negative effects, leading to altered optimal disturbance intervals (the disturbance interval at which population growth rate is highest) and changes in the sensitivity of population growth rate to disturbance interval. While we know that climate may alter impacts of disturbance in some systems, we have a poor understanding of which effects of disturbance and which vital rates might drive an altered response to disturbance interval in a changing climate. We use demographic monitoring of natural populations of Dionaea muscipula, the Venus flytrap, that have experienced natural and managed fires, combined with realistic past and future climate projections, to construct climate- and fire-driven integral projection models (IPMs). We use these IPMs to compare the effect of fire return interval (FRI) on population growth rate in past and future climates. To dissect the mechanisms driving FRI response, we then construct IPMs with demographic data from an experimental manipulation of fire effects (ash addition, neighbor removal) and an accidental fire. Our results show that an FRI of 10 years is optimal for D. muscipula in past climate conditions, but a longer FRI (12 years) is optimal in future climate conditions. Further, deviations from optimal FRI reduce population growth rate dramatically in the past climate, but this reduction is muted in a future climate (future minus past sensitivity = 0.006, 95% CI [0.002, 0.011]). Finally, our experimental work suggests that fire effects are driven in part by positive, additive effects of competitor removal and ash addition immediately following a fire; for one population, both these treatments significantly increased population growth rate. Our work suggests that climate change can alter the response of populations to disturbance, highlighting the need to consider the interacting effects of multiple abiotic drivers when projecting future population growth and geographical distributions.
","language":"English","publisher":"Wiley","doi":"10.1002/ecm.1528","usgsCitation":"Louthan, A.M., Keighron, M., Kiekebusch, E., Cayton, H., Terando, A., and Morris, W., 2022, Climate change weakens the impact of disturbance interval on the growth rate of natural populations of Venus flytrap: Ecological Monographs, v. 92, e1528, 18 p., https://doi.org/10.1002/ecm.1528.","productDescription":"e1528, 18 p.","ipdsId":"IP-114086","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":446451,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecm.1528","text":"Publisher Index Page"},{"id":406517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.310791015625,\n 34.59478059328729\n ],\n [\n -76.7230224609375,\n 34.59478059328729\n ],\n [\n -76.7230224609375,\n 35.018750379438295\n ],\n [\n -77.310791015625,\n 35.018750379438295\n ],\n [\n -77.310791015625,\n 34.59478059328729\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.28970336914062,\n 35.04011643687423\n ],\n [\n -78.8818359375,\n 35.04011643687423\n ],\n [\n -78.8818359375,\n 35.3308118573182\n ],\n [\n -79.28970336914062,\n 35.3308118573182\n ],\n [\n -79.28970336914062,\n 35.04011643687423\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"92","noUsgsAuthors":false,"publicationDate":"2022-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Louthan, Allison M","contributorId":266009,"corporation":false,"usgs":false,"family":"Louthan","given":"Allison","email":"","middleInitial":"M","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":851461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keighron, Melina","contributorId":296421,"corporation":false,"usgs":false,"family":"Keighron","given":"Melina","email":"","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":851462,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kiekebusch, Elsita","contributorId":257676,"corporation":false,"usgs":false,"family":"Kiekebusch","given":"Elsita","email":"","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":851463,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cayton, Heather","contributorId":229344,"corporation":false,"usgs":false,"family":"Cayton","given":"Heather","email":"","affiliations":[{"id":41625,"text":"Kellogg Biological Station and Department of Integrative Biology, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":851464,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Terando, Adam J. 0000-0002-9280-043X","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":216875,"corporation":false,"usgs":true,"family":"Terando","given":"Adam J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":851465,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morris, William F.","contributorId":266011,"corporation":false,"usgs":false,"family":"Morris","given":"William F.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":851466,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70236586,"text":"70236586 - 2022 - A machine learning approach to predicting equilibrium ripple wavelength","interactions":[],"lastModifiedDate":"2022-09-28T16:48:59.256996","indexId":"70236586","displayToPublicDate":"2022-09-12T08:11:32","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7599,"text":"Environmental Modeling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A machine learning approach to predicting equilibrium ripple wavelength","docAbstract":"Sand ripples are geomorphic features on the seafloor that affect bottom boundary layer dynamics including wave attenuation and sediment transport. We present a new equilibrium ripple predictor using a machine learning approach that outputs a probability distribution of wave-generated equilibrium wavelengths and statistics including an estimate of ripple height, the most probable ripple wavelength, and sediment and flow parameterizations. The Bayesian Optimal Model System (BOMS) is an ensemble machine learning system that combines two machine learning algorithms and two deterministic empirical ripple predictors with a Bayesian meta-learner to produce probabilistic wave-generated equilibrium ripple wavelength estimates in sandy locations. A ten-fold cross validation of BOMS resulted in an adjusted R-squared value of 0.93 and an average root mean square error (RMSE) of 8.0 cm. During both cross validation and testing on three unique field datasets, BOMS provided more accurate wavelength predictions than each individual base model and other common ripple predictors.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2022.105509","usgsCitation":"Phillip, R.E., Penko, A.M., Palmsten, M.L., and DuVal, C.B., 2022, A machine learning approach to predicting equilibrium ripple wavelength: Environmental Modeling and Software, v. 157, 105509, 13 p., https://doi.org/10.1016/j.envsoft.2022.105509.","productDescription":"105509, 13 p.","ipdsId":"IP-133890","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446454,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2022.105509","text":"Publisher Index Page"},{"id":406515,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"157","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Phillip, Ryan E.","contributorId":296413,"corporation":false,"usgs":false,"family":"Phillip","given":"Ryan","email":"","middleInitial":"E.","affiliations":[{"id":62875,"text":"U.S. Naval Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":851445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Penko, Allison M.","contributorId":296414,"corporation":false,"usgs":false,"family":"Penko","given":"Allison","email":"","middleInitial":"M.","affiliations":[{"id":62875,"text":"U.S. Naval Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":851446,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palmsten, Margaret L. 0000-0002-6424-2338","orcid":"https://orcid.org/0000-0002-6424-2338","contributorId":239955,"corporation":false,"usgs":true,"family":"Palmsten","given":"Margaret","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":851447,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DuVal, Carter B.","contributorId":296415,"corporation":false,"usgs":false,"family":"DuVal","given":"Carter","email":"","middleInitial":"B.","affiliations":[{"id":62875,"text":"U.S. Naval Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":851448,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70241526,"text":"70241526 - 2022 - Forecasting explosions at Sinabung Volcano, Indonesia, based on SO2 emission rates","interactions":[],"lastModifiedDate":"2023-03-22T11:53:19.487909","indexId":"70241526","displayToPublicDate":"2022-09-12T06:51:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting explosions at Sinabung Volcano, Indonesia, based on SO2 emission rates","docAbstract":"Dome-building volcanic eruptions are often associated with frequent Vulcanian explosions, which constitute a substantial threat to proximal communities. One proposed mechanism driving such explosions is the sealing of the shallow volcanic system followed by pressurization due to gas accumulation beneath the seal. We investigate this hypothesis at Sinabung Volcano (Sumatra, Indonesia), which has been in a state of eruption since August 2010. In 2013, the volcano began erupting a lava dome and lava flow, and frequent explosions produced eruptive columns that rose many kilometers into the atmosphere and at times sent pyroclastic density currents down the southeast flanks. A network of scanning Differential Optical Absorption Spectrometers (DOAS) was installed on the volcano’s eastern flank in 2016 to continuously monitor SO2 emission rates during daytime hours. Analysis of the DOAS data from October 2016 to September 2017 revealed that passive SO2 emissions were generally lower in the 5 days leading up to explosive events (∼100 t/d) than was common in 5-day periods leading up to days on which no explosions occurred (∼200 t/d). The variability of passive SO2 emissions, expressed as the standard deviation, also took on a slightly wider range of values before days with explosions (0–103 t/d at 1-sigma) than before days without explosions (43–117 t/d). These observations are consistent with the aforementioned seal-failure model, where the sealing of the volcanic conduit blocks gas emissions and leads to pressurization and potential Vulcanian explosions. We develop a forecasting methodology that allows calculation of a relative daily explosion probability based solely on measurements of the SO2 emission rate in the preceding days. We then calculate forecast explosion probabilities for the remaining SO2 emissions dataset (October 2017—September 2021). While the absolute accuracy of forecast explosion probabilities is variable, the method can inform the probability of an explosion occurring relative to that on other days in each test period. This information can be used operationally by volcano observatories to assess relative risk. The SO2 emissions-based forecasting method is likely applicable to other open vent volcanoes experiencing dome-forming eruptions.
Climate matching allows comparisons of climatic conditions between different locations to understand location and species range climatic suitability. The approach may be used as part of horizon scanning exercises such as those conducted for invasive species. We implemented the CLIMATCH algorithm into an R package, climatchR. The package allows automated and scripted climate matching exercises across all steps from downloading data to summarizing species climate matches. We also show how climatchR may be used with high-throughput computing to process many species. For example, we were able to calculate climate scores for over 8,000 species in less than 3 days using this package. This automation allows high-throughput processing of species data, a new development for improving the efficiency and speed of climate matching and horizon scanning.
Segmentation of Earth science imagery is an increasingly common task. Among modern techniques that use Deep Learning, the UNet architecture has been shown to be a reliable for segmenting a range of imagery. We developed software–Segmentation Gym–to implement a data-model pipeline for segmentation of scientific imagery using a family of UNet models. With an existing set of imagery and labels, the software uses a single configuration file that handles data set creation, as well as model setup and model training. Key benefits of this software are (a) the focus on reproducible data set creation and modeling, and (b) the ability for quick model experimentation through changes to a configuration file. Quick experimentation permits researchers to prototype different model architectures, sizes, and adjust common hyperparameters to find a suitable model. We demonstrate the use of the software using a data set of 419 labeled Landsat-8 scenes of coastal environments and compare results across two model architectures, five model sizes, and three loss functions. This demonstration highlights that our software enables rapid, reproducible experimentation to determine optimal hyperparameters for specific data sets and research questions.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022EA002332","usgsCitation":"Buscombe, D.D., and Goldstein, E.B., 2022, A reproducible and reusable pipeline for segmentation of geoscientific imagery: Earth and Space Science, v. 9, e2022EA002332, 11 p., https://doi.org/10.1029/2022EA002332.","productDescription":"e2022EA002332, 11 p.","ipdsId":"IP-136939","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446483,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022ea002332","text":"Publisher Index Page"},{"id":408698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2022-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Buscombe, Daniel D. 0000-0001-6217-5584","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":198817,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","middleInitial":"D.","affiliations":[],"preferred":false,"id":855767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldstein, Evan B. 0000-0001-9358-1016","orcid":"https://orcid.org/0000-0001-9358-1016","contributorId":184210,"corporation":false,"usgs":false,"family":"Goldstein","given":"Evan","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":855768,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237158,"text":"70237158 - 2022 - Simulation of heat flow in a synthetic watershed: Lags and dampening across multiple pathways under a climate-forcing scenario","interactions":[],"lastModifiedDate":"2022-10-03T11:38:05.919553","indexId":"70237158","displayToPublicDate":"2022-09-09T06:36:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Simulation of heat flow in a synthetic watershed: Lags and dampening across multiple pathways under a climate-forcing scenario","docAbstract":"1. The relationships between macrophytes and the physical and biological characteristics of the environments that aquatic organisms inhabit are complex. Previous studies have shown that the macrophytes, Ranunculus (subgenus Batrachium), which are dominant in lowland chalk streams and widespread across Europe, can enhance juvenile Atlantic salmon abundance and growth to a greater degree than other physical and biological habitat characteristics. However, mechanistic understanding of how this effect might arise requires consideration of the direct and indirect relationships among habitat characteristics that are likely to be influenced by the presence of macrophyte cover.
2. We applied structural equation modelling to data collected during a 2-year in-river manipulative experiment in the River Frome (southern England, U.K.) designed to quantify the magnitude and the relative importance of direct and indirect influences of Ranunculus cover and other physical and biological variables, including water velocity, water depth, prey biomass and body size, and abundance of con- and hetero-specifics, on abundance and somatic growth of 0+ salmon.
3. Results indicated a strongly positive direct influence of Ranunculus cover on salmon abundance, as well as positive influences of Ranunculus on velocity heterogeneity and water depth that are indirectly related to decreased salmon abundance. Interestingly, there was no indication of a direct influence of Ranunculus cover on salmon growth, although Ranunculus was indirectly related to increased salmon growth through its positive influence on prey biomass, an effect mediated by velocity heterogeneity and proportion of fast velocities.
4. These findings provide novel mechanistic insights into the key role of Ranunculus in their native lowland rivers to enhance abundance and improve conditions for multiple food web components. Strategies to maintain or enhance naturally occurring Ranunculus in these rivers are therefore likely to return wide ranging ecosystem benefits, including for species of high conservation value, such as salmon. These mechanistic impacts on habitat heterogeneity and ecosystem productivity could generalise to native macrophytes in other river systems, particularly where habitat is dominated by vegetation in the absence of large substrates.
Climate change is expected to have a major hydrological impact on the core breeding habitat and migration corridors of many amphibians in the twenty-first century. The Yosemite toad (Anaxyrus canorus) is a species of meadow-specializing amphibian endemic to the high-elevation Sierra Nevada Mountains of California. Despite living entirely on federal lands, it has recently faced severe extirpations, yet our understanding of climatic influences on population connectivity is limited. In this study, we used a previously published double-digest RADseq dataset along with numerous remotely sensed habitat features in a landscape genetics framework to answer two primary questions in Yosemite National Park: (1) Which fine-scale climate, topographic, soil, and vegetation features most facilitate meadow connectivity? (2) How is climate change predicted to influence both the magnitude and net asymmetry of genetic migration? We developed an approach for simultaneously modeling multiple toad migration paths, akin to circuit theory, except raw environmental features can be separately considered. Our workflow identified the most likely migration corridors between meadows and used the unique cubist machine learning approach to fit and forecast environmental models of connectivity. We identified the permuted modeling importance of numerous snowpack-related features, such as runoff and groundwater recharge. Our results highlight the importance of considering phylogeographic structure, and asymmetrical migration in landscape genetics. We predict an upward elevational shift for this already high-elevation species, as measured by the net vector of anticipated genetic movement, and a north-eastward shift in species distribution via the network of genetic migration corridors across the park.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41437-022-00561-x","usgsCitation":"Maier, P., Vandergast, A.G., Ostoja, S.M., Aguilar, A., and Bohonak, A.J., 2022, Landscape genetics of a sub-alpine toad: Climate change predicted to induce upward range shifts via asymmetrical migration corridors: Heredity, v. 129, p. 257-272, https://doi.org/10.1038/s41437-022-00561-x.","productDescription":"16 p.","startPage":"257","endPage":"272","ipdsId":"IP-144739","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":446498,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9613655","text":"External Repository"},{"id":409669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.4668810085783,\n 38.44363766038242\n ],\n [\n -120.4668810085783,\n 36.93160395898977\n ],\n [\n -118.12778648528116,\n 36.93160395898977\n ],\n [\n -118.12778648528116,\n 38.44363766038242\n ],\n [\n -120.4668810085783,\n 38.44363766038242\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"129","noUsgsAuthors":false,"publicationDate":"2022-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Maier, Paul A. 0000-0003-0851-8827","orcid":"https://orcid.org/0000-0003-0851-8827","contributorId":221033,"corporation":false,"usgs":false,"family":"Maier","given":"Paul A.","affiliations":[{"id":40313,"text":"Department of Biology, San Diego State","active":true,"usgs":false}],"preferred":false,"id":857617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ostoja, Steven M sostoja@usgs.gov","contributorId":192955,"corporation":false,"usgs":false,"family":"Ostoja","given":"Steven","email":"sostoja@usgs.gov","middleInitial":"M","affiliations":[],"preferred":false,"id":857619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aguilar, Andres","contributorId":195155,"corporation":false,"usgs":false,"family":"Aguilar","given":"Andres","email":"","affiliations":[],"preferred":false,"id":857620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bohonak, Andrew J.","contributorId":195156,"corporation":false,"usgs":false,"family":"Bohonak","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":857621,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236067,"text":"ofr20221037 - 2022 - Monitoring framework to evaluate effectiveness of aquatic and floodplain habitat restoration activities for native fish along the Willamette River, northwestern Oregon","interactions":[],"lastModifiedDate":"2026-03-30T13:24:47.084148","indexId":"ofr20221037","displayToPublicDate":"2022-09-07T10:20:44","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1037","displayTitle":"Monitoring Framework to Evaluate Effectiveness of Aquatic and Floodplain Habitat Restoration Activities for Native Fish along the Willamette River, Northwestern Oregon","title":"Monitoring framework to evaluate effectiveness of aquatic and floodplain habitat restoration activities for native fish along the Willamette River, northwestern Oregon","docAbstract":"Since 2008, large-scale restoration programs have been implemented along the Willamette River, Oregon, to address historical losses of floodplain habitats caused by dam construction, bank protection, large wood removal, land conversion, and other anthropogenic influences. The Willamette Focused Investment Partnership (WFIP) restoration initiative brings together more than 16 organizations to improve floodplain habitats on more than 35,000 hectares upstream from Willamette Falls with the overarching goal to expand and enhance native fish habitats through the following restoration activities implemented along the floodplains and off-channel areas of the Willamette River: (A) modify floodplain topography and human-made barriers to inundation; (B) enhance gravel pits; (C) remove revetments; (D) construct off-channel features; (E) increase and enhance floodplain forest vegetation; and (F) treat aquatic invasive plant species (AIS). The WFIP Effectiveness Monitoring Program was initiated to inform future refinement of Willamette River restoration program goals and activities and has three goals: (1) evaluate the effectiveness of different restoration activities at increasing and enhancing native fish habitat, (2) improve overall understanding of the physical and ecological responses associated with different restoration activities undertaken by the WFIP, and (3) relate site-scale responses to restoration with broader patterns of fish communities, hydrogeomorphology, stream temperature, and vegetation across the Willamette River floodplain, so that the relative importance of restoration activities on habitat availability for native fish can be assessed.
A monitoring framework was developed to evaluate effectiveness of floodplain restoration activities at increasing and enhancing habitat for native fish in the Willamette River corridor, northwestern Oregon. This framework describes monitoring indicators, metrics, and approaches for evaluating responses in native fish communities and physical habitat conditions to restoration activities and determining effectiveness of restoration activities at improving habitats for native fish. The monitoring indicators and approaches are grouped into five restoration monitoring categories that are useful for characterizing ecological and physical habitat responses to restoration activities: fish, hydrogeomorphology, floodplain forest vegetation, birds, and AIS. This monitoring framework provides a common science foundation to support collaborative decisions on future interdisciplinary effectiveness monitoring activities for Willamette River restoration programs. To evaluate restoration effectiveness, data must be evaluated according to metrics and thresholds that permit direct comparison between habitat conditions at the restoration site and restoration program goals; this framework provides examples of metrics and thresholds for evaluating data, recognizing that the precise evaluation criteria for a particular site or program will need to be tailored to meet program questions and available resources. Refining restoration goals and activities as part of an adaptively managed process requires addressing critical uncertainties between restoration goals, restoration activities, and outcomes for habitats used by native fish. Although the monitoring activities of this framework will generate important datasets useful for evaluating restoration effectiveness, additional research, syntheses, and reporting is ultimately necessary to provide a common science foundation to support adaptively managed restoration programs. This report is intended as a resource for restoration program managers, practitioners, scientists, and contractors as they develop detailed annual monitoring plans for data collection and identify the monitoring indicators, metrics, and approaches that are appropriate for evaluating effectiveness of different restoration activities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221037","collaboration":"Prepared in cooperation with Benton Soil and Water Conservation District and Oregon Watershed Enhancement Board","usgsCitation":"Keith, M.K., Wallick, J.R., Flitcroft, R.L., Kock, T.J., Brown, L.A., Miller, R., Hagar, J.C., Guillozet, K., and Jones, K.L., 2022, Monitoring framework to evaluate effectiveness of aquatic and floodplain habitat restoration activities for native fish along the Willamette River, northwestern Oregon: U.S. Geological Survey Open-File Report 2022–1037, 116 p., https://doi.org/10.3133/ofr20221037.","productDescription":"Report: xi,116 p.; Data Reease","onlineOnly":"Y","ipdsId":"IP-117547","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":501771,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113503.htm","linkFileType":{"id":5,"text":"html"}},{"id":405744,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N55MYW","text":"USGS data release","description":"USGS data release","linkHelpText":"Native and non-native fish species in the Willamette River Basin, Oregon"},{"id":405742,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1037/coverthb.jpg"},{"id":405743,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1037/ofr20221037.pdf","text":"Report","size":"77.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1037"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.42041015624999,\n 43.96119063892024\n ],\n [\n -122.36572265625,\n 43.96119063892024\n ],\n [\n -122.36572265625,\n 45.537136680398596\n ],\n [\n -123.42041015624999,\n 45.537136680398596\n ],\n [\n -123.42041015624999,\n 43.96119063892024\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
For decades there has been a debate about the relative effects of dynamic versus static stress triggering of aftershocks. According to the static Coulomb stress change hypothesis, aftershocks should not occur in stress shadows—regions where static Coulomb stress has been reduced. We show that static stress shadows substantially influence aftershock occurrence following three M ≥ 7 California mainshocks. Within the modeled static Coulomb stress shadows, the aftershock rate is an order of magnitude lower than in the modeled increase regions. However, the earthquake rate in the stress shadows does not decrease below the background rate, as predicted by Coulomb stress change models. Aftershocks in the stress shadows exhibit different spatial–temporal characteristics from aftershocks in the stress increase regions. The aftershock rate in the stress shadows decays as a power law with distance from the mainshock, consistent with a simple model of dynamic stress triggering. These aftershocks begin with a burst of activity during the first few days after the mainshock, also consistent with dynamic stress triggering. Our interpretation is that aftershock sequences are the combined result of static and dynamic stress triggering, with an estimated ∼34% of aftershocks due to dynamic triggering and ∼66% due to static triggering.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320220023","usgsCitation":"Hardebeck, J.L., and Harris, R.A., 2022, Earthquakes in the shadows: Why aftershocks occur at surprising locations: The Seismic Record, v. 2, no. 3, p. 207-216, https://doi.org/10.1785/0320220023.","productDescription":"10 p.","startPage":"207","endPage":"216","ipdsId":"IP-131590","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":446500,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320220023","text":"Publisher Index Page"},{"id":406842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-09-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":254964,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":851948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Ruth A. 0000-0002-9247-0768 harris@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-0768","contributorId":786,"corporation":false,"usgs":true,"family":"Harris","given":"Ruth","email":"harris@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":851949,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70234745,"text":"70234745 - 2022 - Long-term apparent survival of a cold-stunned subpopulation of juveniles green turtles","interactions":[],"lastModifiedDate":"2022-09-13T16:52:50.33253","indexId":"70234745","displayToPublicDate":"2022-09-06T11:50:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Long-term apparent survival of a cold-stunned subpopulation of juveniles green turtles","docAbstract":"Understanding the effects of extreme weather on animal populations is fundamental to ecological and conservation sciences and species management. Climate change has resulted in both warm and cold temperature extremes, including an increased frequency of severe cold snaps at middle latitudes in North America. These unusually cold air masses cause rapid declines in nearshore ocean temperatures in coastal areas, with detrimental effects on marine organisms. Acute cold-stun events (hereafter cold stuns) occur when hundreds to thousands of resident juvenile sea turtles fail to escape shallow water during cold snaps. Human intervention through rescue and recovery largely mitigates direct juvenile sea turtle mortality, but delayed effects of cold stuns on rescued individuals are not well understood. Our objective was to examine long-term juvenile green turtle (Chelonia mydas) survival across four cold stuns of varying severity in St. Joseph Bay, Florida, between 2010 and 2018. We used the classic Cormack–Jolly–Seber model in a hierarchical Bayesian framework to estimate apparent survival (i.e., emigration and mortality) of rescued turtles at different time intervals. Our results indicated about half of a cohort rescued during a severe cold stun in January 2010 likely remained in the population 1 year later, with 10%–20% remaining 4 years later, and as few as 5% by 2018. The results also suggested higher apparent survival for cohorts rescued during two subsequent milder cold stuns. Emigration was a more plausible ecological explanation for low apparent survival than delayed mortality. Potential ecological mechanisms underlying emigration include a reduction in food availability and a behavioral response to either the severe weather event or handling during rescue (or both). However, the typical annual turnover of juvenile green turtles, though assumed low, is not well known in St. Joseph Bay. Thus, our apparent survival estimates may be reflective of higher-than-expected emigration in the broader population. Our study provides important baseline information about long-term juvenile sea turtle survival after cold stuns in temperate regions. We also highlight the importance of strategic monitoring between cold stuns to examine additional ecological questions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4221","usgsCitation":"Mollenhauer, R.M., Lamont, M., and Foley, A.M., 2022, Long-term apparent survival of a cold-stunned subpopulation of juveniles green turtles: Ecosphere, e4221, 14 p., https://doi.org/10.1002/ecs2.4221.","productDescription":"e4221, 14 p.","ipdsId":"IP-133328","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":446509,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4221","text":"Publisher Index Page"},{"id":406608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"St Joseph Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.43243408203125,\n 29.673735421779128\n ],\n [\n -85.29579162597655,\n 29.673735421779128\n ],\n [\n -85.29579162597655,\n 29.891257492496305\n ],\n [\n -85.43243408203125,\n 29.891257492496305\n ],\n [\n -85.43243408203125,\n 29.673735421779128\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-09-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Mollenhauer, Robert Michael 0000-0002-4033-8685","orcid":"https://orcid.org/0000-0002-4033-8685","contributorId":290165,"corporation":false,"usgs":true,"family":"Mollenhauer","given":"Robert","email":"","middleInitial":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":848930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":222403,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":848931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foley, Allen M.","contributorId":195874,"corporation":false,"usgs":false,"family":"Foley","given":"Allen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":848932,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263919,"text":"70263919 - 2022 - A late Cenozoic kinematic model for fault motion within greater Cascadia","interactions":[],"lastModifiedDate":"2025-02-28T15:23:57.809725","indexId":"70263919","displayToPublicDate":"2022-09-06T09:19:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"A late Cenozoic kinematic model for fault motion within greater Cascadia","docAbstract":"Widely accepted tectonic reconstructions indicate at least 100 km of coast-parallel northwestward translation of the Sierra Nevada block of California and 15–20° clockwise rotation of most of Oregon since the current phase of Basin and Range extension began ∼17 Ma. These reconstructions require at least 100 km of convergence between the central Coast Range of Oregon and rigid North America in mainland British Columbia, yet there is little discussion of how such convergence might be distributed. This study offers a kinematic model of the distribution of such deformation, constrained by geodesy, paleomagnetism, and fault offsets in Nevada, California and Oregon. The model includes differential rotation across the thrust faults of the Yakima fold and thrust belt (YFTB), compressive right-lateral faulting in the Washington Cascade Range, substantial thrust faulting within the Puget Lowland, and oroclinal bending and doming in the Olympic Mountains. Shortening across YTFB along 120°W longitude is modeled as 47 km, across Puget Lowland at 123°W (Olympia-Bellingham) is 94 km, and total shortening between the central Oregon Coast Range and northern Washington (Corvallis-Bellingham) is 125 km. Current motion of the coastal regions above the Cascadia subduction zone results from both permanent deformation of the continent and elastic coupling to the subducting plate. Permanent deformation in the model is based on extrapolating geodesy from east of 120°W or south of 40°N, indicating a very uniform convergence velocity with the Juan de Fuca plate for northernmost California and Oregon near 31 mm/yr at N61°E.
","language":"English","publisher":"American Geophysical Union","doi":"/10.1029/2022GC010442","usgsCitation":"Wilson, D.S., and McCrory, P.A., 2022, A late Cenozoic kinematic model for fault motion within greater Cascadia: Geochemistry, Geophysics, Geosystems, v. 23, no. 9, e2022GC010442, 23 p., https://doi.org//10.1029/2022GC010442.","productDescription":"e2022GC010442, 23 p.","ipdsId":"IP-087056","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":487582,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022gc010442","text":"Publisher Index Page"},{"id":482636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Montana, Nevada, Oregon, Washington, Wyoming","otherGeospatial":"Greater Cascadia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.80058361811714,\n 43.705403176608456\n ],\n [\n -112.1830337337602,\n 48.93642761048696\n ],\n [\n -123.20997571125247,\n 49.00068131470371\n ],\n [\n -123.27314338672014,\n 48.315457212705695\n ],\n [\n -124.91769611303806,\n 48.51325876215739\n ],\n [\n -124.10331971880694,\n 45.68741856292945\n ],\n [\n -124.72460678447862,\n 42.471289361135035\n ],\n [\n -124.46584634817447,\n 39.45335870478422\n ],\n [\n -121.48933765727764,\n 35.84317504003066\n ],\n [\n -117.67216197790219,\n 39.37476870569205\n ],\n [\n -113.99622925328066,\n 42.04652529338142\n ],\n [\n -110.09067829159352,\n 42.2589105613539\n ],\n [\n -109.80058361811714,\n 43.705403176608456\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Douglas S.","contributorId":68782,"corporation":false,"usgs":true,"family":"Wilson","given":"Douglas","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":929091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCrory, Patricia A. 0000-0003-2471-0018 pmccrory@usgs.gov","orcid":"https://orcid.org/0000-0003-2471-0018","contributorId":2728,"corporation":false,"usgs":true,"family":"McCrory","given":"Patricia","email":"pmccrory@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":929092,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237771,"text":"70237771 - 2022 - Temporal mismatch in space use by a sagebrush obligate species after large-scale wildfire","interactions":[],"lastModifiedDate":"2022-10-24T13:56:00.43779","indexId":"70237771","displayToPublicDate":"2022-09-06T08:44:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Temporal mismatch in space use by a sagebrush obligate species after large-scale wildfire","docAbstract":"The increase in size and frequency of wildfires in sagebrush steppe ecosystems has significant impacts on sagebrush obligate species. We modeled seasonal habitat use by female greater sage-grouse (Centrocercus urophasianus) in the Trout Creek Mountains of Oregon and Nevada, USA, to identify landscape characteristics that influenced sage-grouse habitat selection and to create predictive surfaces of seasonal use 1 and 7 years postfire. We developed three resource selection function models using GPS location data from 2013 to 2019 for three biologically distinct seasons (breeding, n = 149 individuals: 8 March–12 June; summer, n = 140 individuals: 13 June–20 October; and winter, n = 94 individuals: 21 October–7 March). For all seasons, by the fourth or fifth year postfire, sage-grouse selected for unburned patches more than all other burn severity patches and the use of unburned areas in comparison with burned areas increased through time. During the breeding season, sage-grouse selected for low-sagebrush (Artemisia arbuscula)-dominated ecosystems and areas with low biomass (normalized difference vegetation index). During summer, sage-grouse selected for areas with higher annual and perennial grasses and forb cover, and areas that had higher biomass. During winter, sage-grouse selected for areas of intact sagebrush on less rugged terrain. For the winter and breeding season, there was a positive linear relationship between annual grasses and forb cover through time. Seven years postfire (2019), the area predicted to have a high probability of use in each seasonal range decreased (breeding: 16.4%; summer: 12.2%; and winter: 4.2%), while the area predicted to have low or low-medium probability of use increased (breeding: 14.5%; summer: 22.5%; and winter: 22.8%) when compared to the first year following the wildfire (2013). Our results demonstrated a 4- to 5-year time lag before female sage-grouse adapted to a disturbed landscape began avoiding burned areas more than intact, unburned habitats. This mismatch in ecological response may imply declines in habitat availability for sage-grouse and may destabilize population vital rates. Spatially explicit models can aid in identifying priority areas for restoration efforts and conservation actions to mitigate the impacts of future disturbances.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4179","usgsCitation":"Schuyler, E.M., Hagen, C., Anthony, C.R., Foster, L.J., and Dugger, K., 2022, Temporal mismatch in space use by a sagebrush obligate species after large-scale wildfire: Ecosphere, v. 13, no. 9, e4179, 24 p., https://doi.org/10.1002/ecs2.4179.","productDescription":"e4179, 24 p.","ipdsId":"IP-128782","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"links":[{"id":446515,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4179","text":"Publisher Index Page"},{"id":408640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Oregon","otherGeospatial":"Trout Creek Mountains","geographicExtents":"{\n \"type\": 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A.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":855567,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anthony, Christopher R. 0000-0003-0968-224X","orcid":"https://orcid.org/0000-0003-0968-224X","contributorId":296314,"corporation":false,"usgs":true,"family":"Anthony","given":"Christopher","email":"","middleInitial":"R.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":855568,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foster, Lee J.","contributorId":287180,"corporation":false,"usgs":false,"family":"Foster","given":"Lee","email":"","middleInitial":"J.","affiliations":[{"id":36223,"text":"Oregon Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":855569,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":855570,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236362,"text":"70236362 - 2022 - A conceptual framework to integrate biodiversity, ecosystem function, and ecosystem service models","interactions":[],"lastModifiedDate":"2022-10-31T14:33:51.12053","indexId":"70236362","displayToPublicDate":"2022-09-05T11:06:28","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"A conceptual framework to integrate biodiversity, ecosystem function, and ecosystem service models","docAbstract":"Global biodiversity and ecosystem service models typically operate independently. Ecosystem service projections thus may be overly optimistic because they do not account for the role of biodiversity in maintaining ecological functions underpinning their provision. We review models used in recent global model intercomparison projects and develop a novel model integration framework to more fully account for the role of biodiversity in ecosystem function, a key gap for linking biodiversity changes to ecosystem services. We propose two model integration pathways. The first uses empirical data on biodiversity-ecosystem function relationships to bridge biodiversity and ecosystem function models and could currently be implemented at the global scale. We also propose a trait-based approach involving greater incorporation of biodiversity into ecosystem function models that can be applied to more systems and taxa than the first pathway. Integrating biodiversity, ecosystem function, and ecosystem service modeling will enhance development of policies to meet global sustainability goals.","language":"English","publisher":"Oxford University Press","doi":"10.1093/biosci/biac074","usgsCitation":"Weiskopf, S.R., Myers, B.J., Arce-Plata, M.I., Blanchard, J.L., Ferrier, S., Fulton, E.A., Harfoot, M., Isbell, F., Johnson, J., Mori, A.S., Weng, E., Harmáčková, Z., Londono-Murcia, M.C., Miller, B.W., Pereira, L., and Rosa, I., 2022, A conceptual framework to integrate biodiversity, ecosystem function, and ecosystem service models: BioScience, v. 72, no. 11, p. 1062-1073, https://doi.org/10.1093/biosci/biac074.","productDescription":"12 p.","startPage":"1062","endPage":"1073","ipdsId":"IP-132444","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true},{"id":40927,"text":"North Central Climate Adaptation Science 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This research reviews recent literature through 2021 in which we identify linkages among the major modes of climate variability, in the form of ocean-atmosphere teleconnections, and the impacts to temperature and precipitation of the South-Central United States (SCUSA), consisting of Arkansas, Louisiana, New Mexico, Oklahoma, and Texas. The SCUSA is an important areal focus for this analysis because it straddles the ecotone between humid and arid climates in the United States and has a growing population, diverse ecosystems, robust agricultural and other economic sectors including the potential for substantial wind and solar energy generation. Whereas a need exists to understand atmospheric variability due to the cascading impacts through ecological and social systems, our understanding is complicated by the positioning of the SCUSA between subtropical and extratropical circulation features and the influence of the Pacific and Atlantic Oceans, and the adjacent Gulf of Mexico. The Southern Oscillation (SO), Pacific-North American (PNA) pattern, North Atlantic Oscillation (NAO) and the related Arctic Oscillation (AO), Atlantic Multidecadal Oscillation/Atlantic Multidecadal Variability (AMO/AMV), and Pacific Decadal Oscillation/Pacific Decadal Variability (PDO/PDV) have been shown to be important modulators of temperature and precipitation variables at the monthly, seasonal, and interannual scales, and the intraseasonal Madden-Julian Oscillation (MJO) in the SCUSA. By reviewing these teleconnection impacts in the region alongside updated seasonal correlation maps, this research provides more accessible and comparable results for interdisciplinary use on climate impacts beyond the atmospheric-environmental sciences.","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2022.934654","usgsCitation":"Rohli, R.V., Snedden, G., Martin, E.R., and DeLong, K., 2022, Impacts of ocean-atmosphere teleconnection patterns on the south-central United States: Frontiers in Earth Science, v. 10, 934654, 26 p., https://doi.org/10.3389/feart.2022.934654.","productDescription":"934654, 26 p.","ipdsId":"IP-141149","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":446526,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2022.934654","text":"Publisher Index 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0000-0001-7821-3709","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":216669,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":850840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Elinor R.","contributorId":296175,"corporation":false,"usgs":false,"family":"Martin","given":"Elinor","email":"","middleInitial":"R.","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":850841,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeLong, Kristine L.","contributorId":263459,"corporation":false,"usgs":false,"family":"DeLong","given":"Kristine L.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":850842,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237051,"text":"70237051 - 2022 - New generation hyperspectral data From DESIS compared to high spatial resolution PlanetScope data for crop type classification","interactions":[],"lastModifiedDate":"2022-09-28T15:30:10.811953","indexId":"70237051","displayToPublicDate":"2022-09-05T10:25:32","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1942,"text":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"New generation hyperspectral data From DESIS compared to high spatial resolution PlanetScope data for crop type classification","docAbstract":"Thoroughly investigating the characteristics of new generation hyperspectral and high spatial resolution spaceborne sensors will advance the study of agricultural crops. Therefore, we compared the performances of hyperspectral Deutsches Zentrum fur Luftund Raumfahrt- (DLR) Earth Sensing Imaging Spectrometer (DESIS) and high spatial resolution PlanetScope in classifying eight crop types in California's Central Valley during the 2020 growing season. The DESIS sensor onboard the International Space Station collects data at 235 hyperspectral narrowbands (HNB) each with 2.55 nm bandwidth from 400–1000 nm and 30 m spatial resolution. In contrast, PlanetScope Dove-R data have four multispectral broadbands (MBB) with 3–4 m spatial resolution. We obtained best classification accuracies using 14 DESIS HNB from the August 2020 image, with an overall accuracy of 85% and producer's and user's accuracies of 72–100% and 75–100%, respectively, for the eight crops. The best classification accuracies using PlanetScope data were obtained using an image mosaic pair from June and August 2020; this resulted in an overall accuracy of 79% and producer's and user's accuracies of 56–100% and 61–100%, respectively. Combining the best 14 DESIS HNB from August 2020 with the 4 PlanetScope MBB from August 2020 yielded an overall accuracy of 82% and producer's and user's accuracies of 65–100% and 60–94%, respectively. On one-to-one single date comparisons of DESIS versus PlanetScope data, the hyperspectral data always outperformed high spatial resolution data in crop type classification. Nevertheless, high spatial resolution data will remain invaluable in assessing within-field variability and crop biophysical/biochemical modeling in precision agriculture.
","language":"English","publisher":"IEEE","doi":"10.1109/JSTARS.2022.3204223","usgsCitation":"Aneece, I.P., Foley, D., Thenkabail, P., Oliphant, A., and Teluguntla, P.G., 2022, New generation hyperspectral data From DESIS compared to high spatial resolution PlanetScope data for crop type classification: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, v. 15, p. 7846-7858, https://doi.org/10.1109/JSTARS.2022.3204223.","productDescription":"13 p.","startPage":"7846","endPage":"7858","ipdsId":"IP-140341","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":446530,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1109/jstars.2022.3204223","text":"Publisher Index Page"},{"id":435698,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XM63RK","text":"USGS data release","linkHelpText":"PlanetScope and DESIS spectral library of agricultural crops in California's Central Valley for the 2020 growing season"},{"id":407512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Aneece, Itiya P. 0000-0002-1201-5459","orcid":"https://orcid.org/0000-0002-1201-5459","contributorId":208265,"corporation":false,"usgs":true,"family":"Aneece","given":"Itiya","middleInitial":"P.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":853176,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foley, Daniel 0000-0002-2051-6325","orcid":"https://orcid.org/0000-0002-2051-6325","contributorId":208266,"corporation":false,"usgs":true,"family":"Foley","given":"Daniel","email":"","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":853177,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thenkabail, Prasad 0000-0002-2182-8822","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":220239,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":853178,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliphant, Adam 0000-0001-8622-7932 aoliphant@usgs.gov","orcid":"https://orcid.org/0000-0001-8622-7932","contributorId":192325,"corporation":false,"usgs":true,"family":"Oliphant","given":"Adam","email":"aoliphant@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":853179,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Teluguntla, Pardhasaradhi G. 0000-0001-8060-9841","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":297051,"corporation":false,"usgs":true,"family":"Teluguntla","given":"Pardhasaradhi","email":"","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":853180,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236388,"text":"70236388 - 2022 - Characterization of vegetated and ponded wetlands with implications towards coastal wetland marsh collapse","interactions":[],"lastModifiedDate":"2023-06-08T14:54:19.254192","indexId":"70236388","displayToPublicDate":"2022-09-05T10:14:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1198,"text":"Catena","active":true,"publicationSubtype":{"id":10}},"title":"Characterization of vegetated and ponded wetlands with implications towards coastal wetland marsh collapse","docAbstract":"Coastal wetlands provide numerous ecosystem services; yet these ecosystems are increasingly vulnerable to climate change stressors, especially excessive flooding from sea-level rise and storm events. This study highlights the important contribution of vegetation belowground biomass to marsh stability and identifies loss of vegetation as a critical driver of marsh collapse. We investigated the shear strength of salt marshes and unvegetated interior ponds using a modified cone penetrometer along a chronosequence of wetland marsh collapse (0 to 21 + years following pond formation) to characterize changes in the structural integrity of the marsh soil. Following conversion from vegetated marsh to open water pond, the surficial soils experienced a dramatic loss in shear strength resulting from the loss of vegetation and compaction of soil pore space. The Cone Penetrometer Testing (CPT) data indicate that higher shear strength in the surficial layers of the vegetated marsh sites were never recovered, up to 21 + years following marsh collapse. Coupled with significant elevation loss from marsh collapse, additional sea-level rise, deep subsidence, and reduced sedimentation may contribute to conditions that can exceed critical flooding thresholds, making recovery from marsh collapse difficult or impossible. Therefore, characterizing mechanisms and thresholds of marsh collapse are critical for identifying those coastal marshes that are vulnerable to collapse before conversion from vegetated marsh to open water occurs.","language":"English","publisher":"Elsevier","doi":"10.1016/j.catena.2022.106547","usgsCitation":"Cadigan, J.A., Jafari, N., Stagg, C., Laurenzano, C., Harris, B.D., Meselhe, A.E., Dugas, J., and Couvillion, B., 2022, Characterization of vegetated and ponded wetlands with implications towards coastal wetland marsh collapse: Catena, v. 218, 106547, 9 p.; Data Release, https://doi.org/10.1016/j.catena.2022.106547.","productDescription":"106547, 9 p.; Data Release","ipdsId":"IP-123995","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":446532,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.catena.2022.106547","text":"Publisher Index Page"},{"id":406222,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417830,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EW3N0D"}],"country":"United States","state":"Louisiana","city":"Port Sulphur","otherGeospatial":"Gulf of Mexico, Mississippi River Deltaic Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.98626708984375,\n 29.3067588581613\n ],\n [\n -89.48501586914062,\n 29.3067588581613\n ],\n [\n -89.48501586914062,\n 29.54956657394792\n ],\n [\n -89.98626708984375,\n 29.54956657394792\n ],\n [\n -89.98626708984375,\n 29.3067588581613\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"218","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cadigan, Jack A. 0000-0002-1200-8275","orcid":"https://orcid.org/0000-0002-1200-8275","contributorId":296178,"corporation":false,"usgs":false,"family":"Cadigan","given":"Jack","email":"","middleInitial":"A.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":850851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jafari, Navid H.","contributorId":214730,"corporation":false,"usgs":false,"family":"Jafari","given":"Navid H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":850852,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stagg, Camille 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":220330,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":850853,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laurenzano, Claudia 0000-0003-1406-8658","orcid":"https://orcid.org/0000-0003-1406-8658","contributorId":215853,"corporation":false,"usgs":false,"family":"Laurenzano","given":"Claudia","affiliations":[{"id":25340,"text":"Cherokee Nation Technologies","active":true,"usgs":false}],"preferred":false,"id":850854,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harris, Brian D. 0000-0001-5771-1880","orcid":"https://orcid.org/0000-0001-5771-1880","contributorId":296180,"corporation":false,"usgs":false,"family":"Harris","given":"Brian","email":"","middleInitial":"D.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":850855,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meselhe, Amina E.","contributorId":296186,"corporation":false,"usgs":false,"family":"Meselhe","given":"Amina","email":"","middleInitial":"E.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":850856,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dugas, Jason 0000-0001-6094-7560","orcid":"https://orcid.org/0000-0001-6094-7560","contributorId":205300,"corporation":false,"usgs":true,"family":"Dugas","given":"Jason","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":850857,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Couvillion, Brady 0000-0001-5323-1687","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":222810,"corporation":false,"usgs":true,"family":"Couvillion","given":"Brady","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":850858,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70236363,"text":"70236363 - 2022 - Balancing future renewable energy infrastructure siting and associated habitat loss for migrating whooping cranes","interactions":[],"lastModifiedDate":"2022-09-05T13:24:05.252457","indexId":"70236363","displayToPublicDate":"2022-09-05T08:18:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Balancing future renewable energy infrastructure siting and associated habitat loss for migrating whooping cranes","docAbstract":"The expansion of human infrastructure has contributed to novel risks and disturbance regimes in most ecosystems, leading to considerable uncertainty about how species will respond to altered landscapes. A recent assessment revealed that whooping cranes (Grus americana), an endangered migratory waterbird species, avoid wind-energy infrastructure during migration. However, uncertainties regarding collective impacts of other types of human infrastructure, such as power lines on migration, variable drought conditions, and continued construction of wind energy infrastructure may compromise ongoing recovery efforts for whooping cranes. Droughts are increasing in frequency and severity throughout the whooping crane migration corridor, and the impacts of drought on stopover habitat use are largely unknown. Moreover, decision-based analyses are increasingly advocated to guide recovery planning for endangered species, yet applications remain rare. Using GPS locations from 57 whooping cranes from 2010 through 2016 in the United States Great Plains, we assessed habitat selection and avoidance of potential disturbances during migration relative to drought conditions, and we used these results in an optimization analysis to select potential sites for new wind energy developments that minimize relative habitat loss for whooping cranes and maximize wind energy potential. Drought occurrence and severity varied spatially and temporally across the migration corridor during our study period. Whooping cranes rarely used areas <5 km from human settlements and wind energy infrastructure under both drought and non-drought conditions, and <2 km from power lines during non-drought conditions, with the lowest likelihood of use near wind energy infrastructure. Whooping cranes differed in their selection of wetland and cropland land cover types depending on drought or non-drought conditions. We identified scenarios for wind energy expansion across the migration corridor and in select states, which are robust to uncertain drought conditions, where future loss of highly selected stopover habitats could be minimized under a common strategy. Our approach was to estimate functional habitat loss while integrating current disturbances, potential future disturbances, and uncertainty in drought conditions. Therefore, dynamic models describing potential costs associated with risk-averse behaviors resulting from future developments can inform proactive conservation before population impacts occur.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2022.931260","usgsCitation":"Ellis, K.S., Pearse, A.T., Brandt, D.A., Bidwell, M., Harrell, W.C., Butler, M.J., and Post van der Burg, M., 2022, Balancing future renewable energy infrastructure siting and associated habitat loss for migrating whooping cranes: Frontiers in Ecology and Evolution, v. 10, 931260, 17 p., https://doi.org/10.3389/fevo.2022.931260.","productDescription":"931260, 17 p.","ipdsId":"IP-138784","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":446538,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2022.931260","text":"Publisher Index Page"},{"id":435701,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P902I4WO","text":"USGS data release","linkHelpText":"Whooping crane migration habitat selection disturbance data and maps"},{"id":406216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Montana, Nebraska, North Dakota, South Dakota, Oklahoma, Texas","otherGeospatial":"Great Plains","volume":"10","noUsgsAuthors":false,"publicationDate":"2022-08-12","publicationStatus":"PW","contributors":{"editors":[{"text":"Hamilton, Diana","contributorId":296218,"corporation":false,"usgs":false,"family":"Hamilton","given":"Diana","email":"","affiliations":[{"id":12803,"text":"Mount Allison University","active":true,"usgs":false}],"preferred":false,"id":850888,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Ellis, Kristen S. 0000-0003-2759-3670","orcid":"https://orcid.org/0000-0003-2759-3670","contributorId":251877,"corporation":false,"usgs":true,"family":"Ellis","given":"Kristen","email":"","middleInitial":"S.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":850802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":850803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandt, David A. 0000-0001-9786-307X dbrandt@usgs.gov","orcid":"https://orcid.org/0000-0001-9786-307X","contributorId":149929,"corporation":false,"usgs":true,"family":"Brandt","given":"David","email":"dbrandt@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":850804,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bidwell, Mark T.","contributorId":139204,"corporation":false,"usgs":false,"family":"Bidwell","given":"Mark T.","affiliations":[{"id":12696,"text":"Environmental Canada","active":true,"usgs":false}],"preferred":false,"id":850805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harrell, Wade C.","contributorId":147143,"corporation":false,"usgs":false,"family":"Harrell","given":"Wade","email":"","middleInitial":"C.","affiliations":[{"id":16793,"text":"USFWS, Ecological Services, Austwell, TX","active":true,"usgs":false}],"preferred":false,"id":850806,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Butler, Matthew J.","contributorId":296149,"corporation":false,"usgs":false,"family":"Butler","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":850807,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Post van der Burg, Max 0000-0002-3943-4194","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":216013,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":850808,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70236497,"text":"70236497 - 2022 - Predictive models of selective cattle use of large, burned landscapes in semiarid sagebrush-steppe","interactions":[],"lastModifiedDate":"2022-09-09T12:14:02.910302","indexId":"70236497","displayToPublicDate":"2022-09-05T07:10:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Predictive models of selective cattle use of large, burned landscapes in semiarid sagebrush-steppe","docAbstract":"The fire-exotic annual grass cycle is a severe threat to shrub-steppe rangelands, and a greater understanding of how livestock grazing relates to the problem is needed to guide effective management interventions. Grazing effects vary throughout shrub-steppe rangelands because livestock are selective in their use within pastures. Thus, knowing where cattle are located and concentrate their use in a postfire landscape is important for enhancing plant community resiliency to disturbance and resistance to exotic annual grass invasion. We asked how the distribution and intensity of cattle use varied across 113 000 ha of recently burned, environmentally varied shrub-steppe. Generalized linear mixed effects models were used to determine the relationship of cattle dung (presence/absence and counts), which was recorded during the third to fifth postfire year (after grazing deferment) on 1166 (531-m2) plots, to water sources, burn severity, grass cover, and topographic predictors. Our distribution and intensity of use models revealed similar relationships between cattle use and landscape predictors. Cattle use was greater in areas that were flatter and closer to water and that had moderate burn severity and less heat load and ruggedness. Slope had the strongest effect on cattle use of the predictors. The probability of cattle being present decreased by 10% for every 5° increase in slope until slope exceeded 15°, and then the effect of slope weakened. Despite moderate slopes
Relative Sea Levels (RSLs) derived primarily from marine bivalves near Petermann Glacier, NW Greenland, constrain past regional ice-mass changes through glacial isostatic adjustment (GIA) modeling. Oxygen isotopes measured on bivalves corrected for shell-depth habitat and document changing meltwater input. Rapid RSL fall of up to 62 m/kyr indicates ice loss at or prior to ∼9 ka. Transition to an RSL stillstand starting at ∼6 ka reflects renewed ice-mass loading followed by further mass loss over the past few millennia. GIA simulations of rapid early RSL fall suggest a low regional upper-mantle viscosity. Early loss of grounded ice tracks atmospheric warming and pre-dates the eventual collapse of Petermann Glacier's floating ice tongue near ∼7 ka, suggesting grounding zone stabilization during early phases of deglaciation. We hypothesize mid-Holocene regrowth of regional ice caps in response to cooling and increased precipitation, following loss of the floating shelf ice. Remnants of these ice caps remain present but are now melting.
Ground deformation during caldera collapse at Kīlauea Volcano in 2018 was recorded in unprecedented detail on a network of real-time GNSS (Global Navigation Satellite System) and tilt instruments. Observations informed hazard assessments during the eruption and now yield insight into collapse dynamics and the magma system. The caldera grew in size over 78 days in a series of repeating, quasi-periodic
Double-crested cormorants (Nannopterum auritum) have been implicated as causes of fish population declines in many locations across their breeding range. Two challenges facing managers are identifying fisheries population metrics indicative of cormorant impacts and determining when this evidence becomes actionable. Building upon existing studies, we conducted a meta-analysis of eight data-rich systems across the Laurentian Great Lakes region of the United States for common fish population responses to changes in cormorant abundance. Specifically, we examined trends in mean total female length at age-3 (TL3), female mean length and age at 50 % maturity, and mean age evenness as indicated by Shannon’s Equitability Index. Annual observations for these metrics were independently regressed linearly against cormorant density by system for walleye (Sander vitreus), yellow perch (Perca flavescens), smallmouth bass (Micropterus dolomieu), and northern pike (Esox lucius) populations. TL3 was the most sensitive with 9 of the 14 datasets statistically significant (r2 range 0.29 to 0.86). Maturity metrics were moderately sensitive to trends in cormorant predation with mean total length at 50 % maturity significant in 4 out of 11 datasets (r2 range 0.27–0.41) and mean age at 50 % maturity significant in 3 out of 11 datasets (r2 range 0.12 – 0.51). Least sensitive was age evenness with the Shannon Index significant in 3 out of 12 datasets (r2 typically < 0.25). Of metrics tested, TL3 was the most reliable indicator of changes in cormorant effects despite varying system changes and management responses among locations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2022.08.022","usgsCitation":"Schultz, D.W., Dorr, B.S., Fielder, D.G., Jackson, J.R., and DeBruyne, R.L., 2022, Indicators of fish population responses to avian predation with focus on double-crested cormorants: Journal of Great Lakes Research, v. 48, no. 6, p. 1659-1668, https://doi.org/10.1016/j.jglr.2022.08.022.","productDescription":"10 p.","startPage":"1659","endPage":"1668","ipdsId":"IP-140185","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":467164,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2022.08.022","text":"Publisher Index Page"},{"id":406437,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Minnesota, New York","otherGeospatial":"Bays de Noc, East Lake Ontario, East Vermillion Lake, Lake 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Center","active":true,"usgs":false}],"preferred":false,"id":851265,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fielder, David G.","contributorId":127535,"corporation":false,"usgs":false,"family":"Fielder","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":7024,"text":"Michigan Department of Natural Resources, Fisheries Research Station","active":true,"usgs":false}],"preferred":false,"id":851266,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, James R.","contributorId":55709,"corporation":false,"usgs":false,"family":"Jackson","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":851267,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeBruyne, Robin L. 0000-0002-9232-7937 rdebruyne@usgs.gov","orcid":"https://orcid.org/0000-0002-9232-7937","contributorId":4936,"corporation":false,"usgs":true,"family":"DeBruyne","given":"Robin","email":"rdebruyne@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":851268,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236721,"text":"70236721 - 2022 - Brief oil exposure reduces fitness in wild Gulf of Mexico mahi-mahi (Coryphaena hippurus)","interactions":[],"lastModifiedDate":"2022-09-28T16:51:31.82644","indexId":"70236721","displayToPublicDate":"2022-09-02T08:59:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Brief oil exposure reduces fitness in wild Gulf of Mexico mahi-mahi (Coryphaena hippurus)","title":"Brief oil exposure reduces fitness in wild Gulf of Mexico mahi-mahi (Coryphaena hippurus)","docAbstract":"The Deepwater Horizon (DWH) disaster released 3.19 million barrels of crude oil into the Gulf of Mexico (GOM) in 2010, overlapping the habitat of pelagic fish populations. Using mahi-mahi (Coryphaena hippurus)─a highly migratory marine teleost present in the GOM during the spill─as a model species, laboratory experiments demonstrate injuries to physiology and behavior following oil exposure. However, more than a decade postspill, impacts on wild populations remain unknown. To address this gap, we exposed wild mahi-mahi to crude oil or control conditions onboard a research vessel, collected fin clip samples, and tagged them with electronic tags prior to release into the GOM. We demonstrate profound effects on survival and reproduction in the wild. In addition to significant changes in gene expression profiles and predation mortality, we documented altered acceleration and habitat use in the first 8 days oil-exposed individuals were at liberty as well as a cessation of apparent spawning activity for at least 37 days. These data reveal that even a brief and low-dose exposure to crude oil impairs fitness in wild mahi-mahi. These findings offer new perspectives on the lasting impacts of the DWH blowout and provide insight about the impacts of future deep-sea oil spills.
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