Bayesian statistics is a framework in which our knowledge about unknown quantities of interest (especially parameters) is updated with the information in observed data, though it can also be viewed as simply another method to fit a statistical model. It has become popular in many branches of biology. For context, five of the ten most cited papers in Web of Science with keywords 'Bayesian statistics' are related to biology (as of August 19, 2024). Bayesian statistics is particularly valuable for biology because it allows researchers to incorporate prior knowledge, handle complex systems, and work effectively with limited or messy data. However, most biologists are trained in frequentist techniques, and the learning curve to become fluent in Bayesian statistics may be perceived as too time-consuming to undertake, or the prospect of adopting an unfamiliar statistical framework can simply appear too daunting. We provide a list of 10 tips to help you get started with Bayesian statistics. You can also refer to the Glossary for definitions of the technical terms. This paper isn’t just for newcomers; even those with some experience in Bayesian methods may find it a useful roadmap to design, conduct, and publish Bayesian analyses. We’ve drawn mainly on our experience teaching and working with ecologists, but we hope these tips will be relevant to a broader audience of biologists. For those seeking to deepen their understanding, we point to more comprehensive resources that offer in-depth exploration of Bayesian statistics.
","language":"English","publisher":"HAL Open Science","usgsCitation":"Gimenez, O., Royle, A., Kery, M., and Nater, C., 2024, Ten quick tips to get you started with Bayesian statistics: HAL Open Science.","productDescription":"15 p.","ipdsId":"IP-174716","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":483930,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://hal.science/hal-04731240v1"},{"id":483932,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gimenez, Olivier","contributorId":352825,"corporation":false,"usgs":false,"family":"Gimenez","given":"Olivier","affiliations":[{"id":16636,"text":"CNRS","active":true,"usgs":false}],"preferred":false,"id":932231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":932232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kery, Marc","contributorId":168361,"corporation":false,"usgs":false,"family":"Kery","given":"Marc","affiliations":[{"id":12551,"text":"Swiss Ornithological Institute, Sempach, Switzerland","active":true,"usgs":false}],"preferred":false,"id":932233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nater, Chloe","contributorId":352861,"corporation":false,"usgs":false,"family":"Nater","given":"Chloe","affiliations":[{"id":33046,"text":"Norwegian Institute for Nature Research","active":true,"usgs":false}],"preferred":false,"id":932234,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70259737,"text":"70259737 - 2024 - Phenology forecasting models for detection and management of invasive annual grasses","interactions":[],"lastModifiedDate":"2024-10-22T12:13:11.576621","indexId":"70259737","displayToPublicDate":"2024-10-10T07:11:39","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Phenology forecasting models for detection and management of invasive annual grasses","docAbstract":"Non-native annual grasses can dramatically alter fire frequency and reduce forage quality and biodiversity in the ecosystems they invade. Effective management techniques are needed to reduce these undesirable invasive species and maintain ecosystem services. Well-timed management strategies, such as grazing, that are applied when invasive grasses are active prior to native plants can control invasive species spread and reduce their impact; however, anticipating the timing of key phenological stages that are susceptible to management over vast landscapes is difficult, as the phenology of these species can vary greatly over time and space. To address this challenge, we created range-wide phenology forecasts for two problematic invasive annual grasses: cheatgrass (Bromus tectorum), and red brome (Bromus rubens). We tested a suite of 18 mechanistic phenology models using observations from monitoring experiments, volunteer science, herbarium records, timelapse camera imagery, and downscaled gridded climate data to identify the models that best predicted the dates of flowering and senescence of the two invasive grass species. We found that the timing of flowering and senescence of cheatgrass and red brome were best predicted by photothermal time models that had been adjusted for topography using gridded continuous heat-insolation load index values. Phenology forecasts based on these models can help managers make decisions about when to schedule management actions such as grazing to reduce undesirable invasive grasses and promote forage production, quality, and biodiversity in grasslands; to predict the timing of greatest fire risk after annual grasses dry out; and to select remote sensing imagery to accurately map invasive grasses across topographic and latitudinal gradients. These phenology models also have the potential to be operationalized for within-season or within-year decision support.
The movement of large amounts of nutrients by migrating animals has ecological benefits for recipient food webs1,2 that may be offset by co-transported contaminants3,4. Salmon spawning migrations are archetypal of this process, carrying marine-derived materials to inland ecosystems where they stimulate local productivity but also enhance contaminant exposure5,6,7. Pacific salmon abundance and biomass are higher now than in the last century, reflecting substantial shifts in community structure8 that probably altered nutrient versus contaminant delivery. Here we combined nutrient and contaminant concentrations with 40 years of annual Pacific salmon returns to quantify how changes in community structure influenced marine to freshwater inputs to western North America. Salmon transported tonnes of nutrients and kilograms of contaminants to freshwaters annually. Higher salmon returns (1976–2015) increased salmon-derived nutrient and contaminant inputs by 30% and 20%, respectively. These increases were dominated by pink salmon, which are short-lived, feed lower in marine food webs than other salmon species, and had the highest nutrient-to-contaminant ratios. As a result, the delivery of nutrients increased at a greater rate than the delivery of contaminants, and salmon inputs became more ecologically beneficial over time. Even still, contaminant loadings may represent exposure concerns for some salmon predators. The Pacific salmon example demonstrates how long-term environmental changes interact with nutrient and contaminant movement across large spatial scales and provides a model for exploring similar patterns with other migratory species.
","language":"English","publisher":"Nature","doi":"10.1038/s41586-024-07980-2","usgsCitation":"Brandt, J.E., Wesner, J., Ruggerone, G., Jardine, T.D., Eagles-Smith, C., Ruso, G., Stricker, C.A., Voss, C.A., and Walters, D., 2024, Continental-scale nutrient and contaminant delivery by Pacific salmon: Nature, v. 634, p. 875-882, https://doi.org/10.1038/s41586-024-07980-2.","productDescription":"8 p.","startPage":"875","endPage":"882","ipdsId":"IP-154909","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":466869,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41586-024-07980-2","text":"Publisher Index Page"},{"id":462785,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"634","noUsgsAuthors":false,"publicationDate":"2024-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Brandt, Jessica E.","contributorId":329987,"corporation":false,"usgs":false,"family":"Brandt","given":"Jessica","email":"","middleInitial":"E.","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":915519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wesner, Jeff S.","contributorId":268319,"corporation":false,"usgs":false,"family":"Wesner","given":"Jeff S.","affiliations":[{"id":55622,"text":"University of South Dakota, Department of Biology, 414 E. Clark St., Vermillion, SD","active":true,"usgs":false}],"preferred":false,"id":915520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruggerone, Gregory T.","contributorId":345066,"corporation":false,"usgs":false,"family":"Ruggerone","given":"Gregory T.","affiliations":[{"id":82477,"text":"Natural Resources Consultants, Inc.","active":true,"usgs":false}],"preferred":false,"id":915521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jardine, Timothy D.","contributorId":305313,"corporation":false,"usgs":false,"family":"Jardine","given":"Timothy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":915522,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":915525,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ruso, Gabrielle E.","contributorId":345067,"corporation":false,"usgs":false,"family":"Ruso","given":"Gabrielle E.","affiliations":[{"id":13706,"text":"University of Missouri-Columbia","active":true,"usgs":false}],"preferred":false,"id":915523,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":915526,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Voss, Cristofor A.","contributorId":345068,"corporation":false,"usgs":false,"family":"Voss","given":"Cristofor","email":"","middleInitial":"A.","affiliations":[{"id":50031,"text":"Regis University","active":true,"usgs":false}],"preferred":false,"id":915524,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Walters, David 0000-0002-4237-2158","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":203410,"corporation":false,"usgs":true,"family":"Walters","given":"David","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":915527,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70259588,"text":"70259588 - 2024 - Discerning sediment provenance in the Outer Banks (USA) through detrital zircon geochronology","interactions":[],"lastModifiedDate":"2024-10-16T11:46:42.605329","indexId":"70259588","displayToPublicDate":"2024-10-09T06:44:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Discerning sediment provenance in the Outer Banks (USA) through detrital zircon geochronology","docAbstract":"Disentangling the influences of climate change from other stressors affecting the population dynamics of aquatic species is particularly pressing for northern latitude ecosystems, where climate-driven warming is occurring faster than the global average. Chinook salmon (Oncorhynchus tshawytscha) in the Yukon-Kuskokwim (YK) region occupy the northern extent of their species' range and are experiencing prolonged declines in abundance resulting in fisheries closures and impacts to the well-being of Indigenous people and local communities. These declines have been associated with physical (e.g., temperature, streamflow) and biological (e.g., body size, competition) conditions, but uncertainty remains about the relative influence of these drivers on productivity across populations and how salmon–environment relationships vary across watersheds. To fill these knowledge gaps, we estimated the effects of marine and freshwater environmental indicators, body size, and indices of competition, on the productivity (adult returns-per-spawner) of 26 Chinook salmon populations in the YK region using a Bayesian hierarchical stock-recruitment model. Across most populations, productivity declined with smaller spawner body size and sea surface temperatures that were colder in the winter and warmer in the summer during the first year at sea. Decreased productivity was also associated with above average fall maximum daily streamflow, increased sea ice cover prior to juvenile outmigration, and abundance of marine competitors, but the strength of these effects varied among populations. Maximum daily stream temperature during spawning migration had a nonlinear relationship with productivity, with reduced productivity in years when temperatures exceeded thresholds in main stem rivers. These results demonstrate for the first time that well-documented declines in body size of YK Chinook salmon were associated with declining population productivity, while taking climate into account.
Non-spatial models of competition between floating aquatic vegetation (FAV) and submersed aquatic vegetation (SAV) predict a stable state of pure SAV at low total available limiting nutrient level, N, a stable state of only FAV for high N, and alternative stable states for intermediate N, as described by an S-shaped bifurcation curve. Spatial models that include physical heterogeneity of the waterbody show that the sharp transitions between these states become smooth. We examined the effects of heterogeneous initial conditions of the vegetation types. We used a spatially explicit model to describe the competition between the vegetation types. In the model, the FAV, duckweed (L. gibba), competed with the SAV, Nuttall's waterweed (Elodea nuttallii). Differences in the initial establishment of the two macrophytes affected the possible stable equilibria. When initial biomasses of SAV and FAV differed but each had the same initial biomass in each spatial cell, the S-shaped bifurcation resulted, but the critical transitions on the N-axis are shifted, depending on FAV:SAV biomass ratio. When the initial biomasses of SAV and FAV were randomly heterogeneously distributed among cells, the vegetation pattern of the competing species self-organized spatially, such that many different stable states were possible in the intermediate N region. If N was gradually increased or decreased through time from a stable state, the abrupt transitions of non-spatial models were changed into smoother transitions through a series of stable states, which resembles the Busse balloon observed in other systems.
Designated in 1978, Kaloko-Honokōhau National Historical Park is located on the west coast of the Island of Hawaiʻi. The Kaloko-Honokōhau National Historical Park encompasses about 1,200 acres of coastal land and nearshore ecosystems, which include wetlands, anchialine pools (landlocked bodies of brackish water with hydrologic connections to the ocean), fishponds, a fishtrap, and coral reefs. These nearshore ecosystems are dependent on groundwater discharge with a freshwater component and provide habitat for threatened and endangered, endemic species, such as the orangeblack Hawaiian damselfly (Megalagrion xanthomelas) and the Hawaiian coot (ʻAlae keʻokeʻo, Fulica alai). The populations of these native species, however, are threatened because of habitat loss related to urban development and environmental changes. Kaloko-Honokōhau National Historical Park is within the Keauhou aquifer system and the North Kona District, which experienced a 52 percent resident-population increase between 2000 and 2020 and a 41 percent visitor increase between 2008 and 2019. To support the current water demand associated with this growing population, groundwater is the primary source of freshwater used in the North Kona District, with about 15 million gallons of groundwater withdrawn from the Keauhou aquifer system per day since 2009. With anticipated development, future (2015–35) groundwater withdrawal from the Keauhou aquifer system is projected to be about 55 percent greater than recent (2012–14) withdrawal. Because Kaloko-Honokōhau National Historical Park is located within a coastal aquifer, natural and human-induced changes can affect the quality and quantity of groundwater, which can threaten groundwater-dependent ecosystems.
To improve understanding of recent groundwater conditions, the U.S. Geological Survey, in cooperation with the National Park Service, undertook this study to document correlations between hydrologic time-series datasets from sites in and near Kaloko-Honokōhau National Historical Park using the nonparametric (distribution-free) Kendall’s tau statistical test.
For the statistical analyses, dependent variables representing the groundwater system include groundwater level, the groundwater-level difference between pairs of sites, and specific conductance, and independent variables include datasets of sea level, rainfall, and groundwater withdrawal. About 34 percent of the 140 non-time-lagged Kendall’s tau statistical tests evaluated in this report are statistically significant (p-value ≤ 0.050) with generally weak (0.1 ≤ tau ≤ 0.2) to moderate (0.2 ≤ tau ≤ 0.3) correlations. Groundwater levels measured at monitoring sites have the strongest correlation with the multivariate El Niño–Southern Oscillation index and withdrawal from production wells at the nearby Kohanaiki Private Club Community. Specific conductance is not consistently and significantly correlated with the independent hydrologic variables investigated in this report.
Because the relations between hydrologic variables are commonly not instantaneous, a second set of correlations was evaluated after applying a range of time lags to the independent variable datasets. Relative to the non-time-lagged case (the set of correlations that did not use time-lagged independent variables), some of the time-lagged independent variables improved correlations with some of the dependent variables. For a particular independent variable, similar time lags were expected between the independent variable and dependent variable at all four monitoring sites. However, different time lags among the four sites sometimes produced the strongest correlations.
This study identified several correlations that are statistically significant and hydrologically plausible, but the correlations could indicate that multiple concurrent factors are controlling the observed groundwater-system response, which might be better addressed using multivariate analyses. This study only investigates bivariate correlations, which may not explain all the variance in the data. The correlations analyzed in this report are limited by the quantity of available hydrologic data in the area near Kaloko-Honokōhau National Historical Park and are based on 14 years of time-series data, which were aggregated to a relatively coarse monthly temporal resolution that represents the minimum resolution common to all datasets.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245084","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Okuhata, B.K., and Oki, D.S., 2024, Correlation analysis of groundwater and hydrologic data, Kaloko-Honokōhau National Historical Park, Hawai‘i: U.S. Geological Survey Scientific Investigations Report 2024–5084, 38 p., https://doi.org/10.3133/sir20245084.","productDescription":"ix, 38 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-154287","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":462626,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5084/covrthb.jpg"},{"id":462627,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5084/sir20245084.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":462628,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5084/sir20245084.xml"},{"id":462629,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5084/images"},{"id":462630,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245084/full"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kaloko-Honokōhau National Historical Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.083351222759,\n 19.721737271204077\n ],\n [\n -156.083351222759,\n 19.65199485292854\n ],\n [\n -155.98955903724118,\n 19.65199485292854\n ],\n [\n -155.98955903724118,\n 19.721737271204077\n ],\n [\n -156.083351222759,\n 19.721737271204077\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
One Health aims to achieve optimal health outcomes for people, animals, plants, and shared environments. We describe a multisector effort to understand and mitigate SARS-CoV-2 transmission risk to humans via the spread among and between captive and wild white-tailed deer. We first framed a One Health problem with three governance sectors that manage captive deer, wild deer populations, and public health. The problem framing included identifying fundamental objectives, causal chains for transmission, and management actions. We then developed a dynamic model that linked deer herds and simulated SARS-CoV-2. Next, we evaluated management alternatives for their ability to reduce SARS-CoV-2 spread in white-tailed deer. We found that single-sector alternatives reduced transmission, but that the best-performing alternative required collaborative actions among wildlife management, agricultural management, and public health agencies. Here, we show quantitative support that One Health actions outperform single-sector responses, but may depend on coordination to track changes in this evolving system.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-024-52737-0","usgsCitation":"Cook, J.D., Rosenblatt, E., DiRenzo, G.V., Campbell Grant, E.H., Mosher, B., Arce, F., Christensen, S., Ghai, R.R., and Runge, M.C., 2024, One Health collaboration is more effective than single-sector actions at mitigating SARS-CoV-2 in deer: Nature Communications, v. 15, 8677, 8 p., https://doi.org/10.1038/s41467-024-52737-0.","productDescription":"8677, 8 p.","ipdsId":"IP-156865","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":460219,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1038/s41467-024-52737-0","text":"External Repository"},{"id":465489,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","noUsgsAuthors":false,"publicationDate":"2024-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Cook, Jonathan D. 0000-0001-7000-8727","orcid":"https://orcid.org/0000-0001-7000-8727","contributorId":291411,"corporation":false,"usgs":true,"family":"Cook","given":"Jonathan","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":909909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenblatt, Elias","contributorId":342124,"corporation":false,"usgs":false,"family":"Rosenblatt","given":"Elias","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":909910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":909911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":909912,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mosher, Brittany A.","contributorId":342963,"corporation":false,"usgs":false,"family":"Mosher","given":"Brittany A.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":909913,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Arce, Fernando","contributorId":342247,"corporation":false,"usgs":false,"family":"Arce","given":"Fernando","email":"","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":909914,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Christensen, Sonja","contributorId":171608,"corporation":false,"usgs":false,"family":"Christensen","given":"Sonja","email":"","affiliations":[{"id":16900,"text":"Massachusetts Division of Fisheries and Wildlife","active":true,"usgs":false}],"preferred":false,"id":909915,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ghai, Ria R.","contributorId":252886,"corporation":false,"usgs":false,"family":"Ghai","given":"Ria","email":"","middleInitial":"R.","affiliations":[{"id":50460,"text":"U.S. Centers for Disease Control and Prevention, Atlanta, GA, United States (","active":true,"usgs":false}],"preferred":false,"id":909916,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":909917,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70261889,"text":"70261889 - 2024 - Distribution and trends of endemic Hawaiian waterbirds, 1986–2023","interactions":[],"lastModifiedDate":"2024-12-31T16:26:54.091554","indexId":"70261889","displayToPublicDate":"2024-10-07T10:19:20","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":138,"text":"Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"HCSU-113","title":"Distribution and trends of endemic Hawaiian waterbirds, 1986–2023","docAbstract":"This study updates the status assessment of four endemic endangered Hawaiian waterbird species—ae‘o (Hawaiian stilt, Himantopus mexicanus knudseni), ‘alae ke‘oke‘o (Hawaiian coot, Fulica alai), ‘alae ‘ula (Hawaiian gallinule, Gallinula galeata sandvicensis), and koloa maoli (Hawaiian duck, Anas wyvilliana)—from 1986 to 2016 by incorporating new data from 2017–2023. State-space models, which account for biological and sampling variation, were fitted to estimate population sizes and trends from both core and non-core wetland survey sites. Long-term trends (1986–2023) largely show increasing populations for all four species, but recent short-term trajectories (2013–2023) are to a greater degree than previous analyses, predominantly negative, indicating accentuated declines in some island populations. Summer counts have declined relative to winter counts over the 38-year period, indicating potential changes in habitat availability and breeding patterns due to shifting rainfall patterns. Although negative trends were apparent in some non-core wetlands, our study underscores the importance of both core and non-core wetlands for waterbird populations.
","language":"English","publisher":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","usgsCitation":"Gorresen, P., Camp, R.J., and Paxton, E.H., 2024, Distribution and trends of endemic Hawaiian waterbirds, 1986–2023: Technical Report HCSU-113, iv, 36 p.","productDescription":"iv, 36 p.","ipdsId":"IP-170387","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":465560,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/10790/5396"},{"id":465574,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gorresen, P. Marcos 0000-0002-0707-9212","orcid":"https://orcid.org/0000-0002-0707-9212","contributorId":196628,"corporation":false,"usgs":false,"family":"Gorresen","given":"P. Marcos","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":922162,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":922163,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paxton, Eben H. 0000-0001-5578-7689","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":19640,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben","email":"","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":922164,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70270828,"text":"70270828 - 2024 - Temperature-driven convergence and divergence of ecohydrological dynamics in the ecosystems of a sky island mountain range","interactions":[],"lastModifiedDate":"2025-08-25T15:00:00.72447","indexId":"70270828","displayToPublicDate":"2024-10-07T09:54:52","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Temperature-driven convergence and divergence of ecohydrological dynamics in the ecosystems of a sky island mountain range","docAbstract":"Forest and woodland decline is predicted to be increasingly influenced by meteorological variation and climate change in the future. By determining how meteorological variation leads to similar versus differing ecohydrological dynamics of forest and woodland ecosystems, we can gain insight on how future climate-driven declines may be realized. We characterized 23 mixed conifer forest (MC), ponderosa pine forest (PP) and piñon pine–juniper woodland (PJ) sites with different canopy covers in southern Nevada, USA. We compared meteorological variation between these sites and employed water balance modelling and information theory to estimate similarity in the density distributions of soil temperature (Ts), soil water potential (SWP) and transpiration partitioning into total evapotranspiration (T/ET) within and across ecosystems in wetter and drier seasons and in cooler and warmer decades. From 1941 to 2020, this location experienced declines in meteorological water deficit due to higher precipitation, although temperatures increased over more recent time periods (1981–2020). From 1981 to 2020, we generally found greater similarity in SWP and T/ET distributions within MC sites and PP sites in the cool season and in the warm season generally found greater similarity in Ts and T/ET distributions within and between PP and PJ sites (excepting T/ET between PJ sites and higher canopy cover PP sites). Recent warm decades promoted convergence in warm and cool season Ts dynamics, such that Ts dynamics generally became more similar between higher elevation MC sites and lower elevation PP–PJ sites. At the same time, warmer decades initiated divergence of SWP and T/ET dynamics within groups of MC–PP and PP–PJ sites that were formerly more similar to each other (excepting SWP in wet seasons). Although their dynamics will remain strongly coupled to precipitation, warming temperatures have the potential to promote divergence in the ecohydrological dynamics of ecosystems at lower and higher elevations in this sky island system and may also promote novel within-ecosystem divergence associated with variation in vegetation structural attributes.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.2703","usgsCitation":"Petrie, M., Bradford, J.B., and Schlaepfer, D.R., 2024, Temperature-driven convergence and divergence of ecohydrological dynamics in the ecosystems of a sky island mountain range: Ecohydrology, v. 17, no. 7, e2703, 20 p., https://doi.org/10.1002/eco.2703.","productDescription":"e2703, 20 p.","ipdsId":"IP-164379","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":494739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.95435956484613,\n 36.566365259428736\n ],\n [\n -115.95435956484613,\n 36.25503150669982\n ],\n [\n -115.03667455367618,\n 36.34361887573249\n ],\n [\n -115.04986536016149,\n 36.59813625773428\n ],\n [\n -115.95435956484613,\n 36.566365259428736\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Petrie, M.D.","contributorId":192983,"corporation":false,"usgs":false,"family":"Petrie","given":"M.D.","email":"","affiliations":[],"preferred":false,"id":947152,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":222784,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":947153,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":947154,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70261247,"text":"70261247 - 2024 - Factors affecting the density of Metabetaeus lohena (Decapoda: Alpheidae) at a high-density anchialine pool environment on the Kona Coast of the Island of Hawai‘i","interactions":[],"lastModifiedDate":"2024-12-03T15:41:40.773375","indexId":"70261247","displayToPublicDate":"2024-10-07T09:34:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2990,"text":"Pacific Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Factors affecting the density of Metabetaeus lohena (Decapoda: Alpheidae) at a high-density anchialine pool environment on the Kona Coast of the Island of Hawai‘i","title":"Factors affecting the density of Metabetaeus lohena (Decapoda: Alpheidae) at a high-density anchialine pool environment on the Kona Coast of the Island of Hawai‘i","docAbstract":"Caridean shrimps (Caridea) are the dominant macroinvertebrates in most anchialine ecosystems. Hawaiian anchialine ecosystems, primarily composed of shallow surface pools connected to the ocean via hypogeal networks of cracks, tubes, and other voids, support 10 caridean shrimp species, including two federally listed as endangered. Little is known about most of these species. The objective of this study was to identify factors that affect the abundance and distribution of Metabetaeus lohena (Alpheidae), an uncommon species found across the Hawaiian Archipelago, at Kaloko-Honokōhau National Historical Park, Island of Hawai‘i. This park supports the highest concentration of anchialine pools in the State of Hawai‘i and is critical to protecting this threatened ecosystem. During 2017, we measured the density of M. lohena during nighttime surveys, as well as a variety of other biological, physical, and chemical parameters, in 130 pools. Metabetaeus lohena occupied 71.5% of the pools surveyed, with a mean density of 7.32 individuals/m2 (95% CI = 5.14–9.49). Invasive fish and the endemic shrimp Halocaridina rubra (Atyidae) had the strongest effects on M. lohena density, with negative and positive relations, respectively. In the first estimate of M. lohena density at this scale, our data indicate that Kaloko-Honokōhau supports about 11,480 shrimp (95% CI = 8,054–14,906) in the pools surveyed. Furthermore, our models predict that this park could support an additional 1,695 individuals (95% CI = 955–3,008) for a population of about 13,175 shrimp if fish were removed from 19 pools in which M. lohena are absent.
","language":"English","publisher":"University of Hawai‘i Press","doi":"10.2984/78.1.3","usgsCitation":"Peck, R., Nash, S., and Camp, R.J., 2024, Factors affecting the density of Metabetaeus lohena (Decapoda: Alpheidae) at a high-density anchialine pool environment on the Kona Coast of the Island of Hawai‘i: Pacific Science, v. 78, no. 1, p. 31-50, https://doi.org/10.2984/78.1.3.","productDescription":"20 p.","startPage":"31","endPage":"50","ipdsId":"IP-158801","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":464700,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kona Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.05239248373394,\n 19.71137367174458\n ],\n [\n -156.04044158152044,\n 19.60032938069341\n ],\n [\n -155.96873616824,\n 19.60032938069341\n ],\n [\n -155.9767034363823,\n 19.712874064167337\n ],\n [\n -156.05239248373394,\n 19.71137367174458\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"78","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peck, Robert W. 0000-0002-8739-9493","orcid":"https://orcid.org/0000-0002-8739-9493","contributorId":193088,"corporation":false,"usgs":false,"family":"Peck","given":"Robert W.","affiliations":[],"preferred":false,"id":920103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nash, Sarah","contributorId":300993,"corporation":false,"usgs":false,"family":"Nash","given":"Sarah","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":920104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":920105,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70259594,"text":"70259594 - 2024 - A \"Region-Specific Model Adaptation (RSMA)\" based training data method in large-scale land cover mapping","interactions":[],"lastModifiedDate":"2024-10-16T12:00:27.443272","indexId":"70259594","displayToPublicDate":"2024-10-06T06:59:29","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"A \"Region-Specific Model Adaptation (RSMA)\" based training data method in large-scale land cover mapping","docAbstract":"The challenge of selecting strategies to adapt to climate change is complicated by the presence of irreducible uncertainties regarding future conditions. Decisions regarding long-term investments in conservation actions contain significant risk of failure due to these inherent uncertainties. To address this challenge, decision makers need an arsenal of sophisticated but practical tools to help guide spatial conservation strategies. Theory asserts that managing risks can be achieved by diversifying an investment portfolio to include assets – such as stocks and bonds – that respond inversely to one another under a given set of conditions. We demonstrate an approach for formalizing the diversification of conservation assets (land parcels) and actions (restoration, species reintroductions) by using correlation structure to quantify the degree of risk for any proposed management investment. We illustrate a framework for identifying future habitat refugia by integrating species distribution modeling, scenarios of climate change and sea level rise, and impacts to critical habitat. Using the plains coqui (Eleutherodactylus juanariveroi), an endangered amphibian known from only three small wetland populations on Puerto Rico’s coastal plains, we evaluate the distribution of potential refugia under two model parameterizations and four future sea-level rise scenarios. We then apply portfolio theory using two distinct objective functions and eight budget levels to inform investment strategies for mitigating risk and increasing species persistence probability. Models project scenario-specific declines in coastal freshwater wetlands from 2% to nearly 30% and concurrent expansions of transitional marsh and estuarine open water. Conditional on the scenario, island-wide species distribution is predicted to contract by 25% to 90%. Optimal portfolios under the first objective function – benefit maximization – emphasizes translocating frogs to existing protected areas rather than investing in the protection of new habitat. Alternatively, optimal strategies using the second objective function – a risk-benefit tradeoff framework – include significant investment to protect parcels for the purpose of reintroduction or establishing new populations. These findings suggest that leveraging existing protected areas for species persistence, while less costly, may contain excessive risk and could result in diminished conservation benefits. Although our modeling includes numerous assumptions and simplifications, we believe this framework provides useful inference for exploring resource dynamics and developing robust adaptation strategies using an approach that is generalizable to other conservation problems which are spatial or portfolio in nature and subject to unresolvable uncertainty.
Segmented barrier islands can be found in regions with small tidal ranges. In contrast to tidally dominated barriers, where inlet dynamics are thought to control island length scales, the controls on barrier island length scales in wave-dominated environments have not been quantified. These microtidal barriers typically have a curved shoreline, suggesting the influence of wave-driven alongshore sediment transport. Microtidal barriers are also typically hydrodynamically isolated from one another, as weak tidal flows limit interactions between adjoining barriers. To better understand the controls on and scales of barrier segmentation in the relative absence of tides, here we develop a theoretical framework to estimate the alongshore length scales at which a barrier will either breach or heal following a disturbance in the barrier morphology. The non-dimensional framework compares the timescales of overwash (advective) and alongshore sediment transport (diffusive) processes along barrier island chains. We then apply this framework to modern barrier islands in the microtidal Gulf of Mexico using wave hindcast data and the lengths, widths, heights, and lagoon depths measured from remotely sensed geospatial data and topobathymetric data. We find that most of these barriers are currently longer than their critical length scale, often as a result of coastal restoration efforts. Our critical length scale analysis suggests that most of the Gulf of Mexico barriers are vulnerable to segmentation despite coastal restoration efforts intended to protect fisheries and the mainland coasts.
Mangroves can increase their elevation relative to tidal flooding through biogeomorphic feedbacks but can submerge if rates of sea-level rise are too great. There is an urgent need to understand the vulnerability of mangroves to sea-level rise so local communities and resource managers can implement and prioritize actions. The need is especially pressing for small islands, which have been identified as an area of concern by the IPCC. We developed a generalizable modeling framework for tidal wetlands (WARMER-3) that accounts for species interactions and the belowground processes that dictate soil elevation building relative to sea levels. The model was calibrated with extensive field datasets, including accretion rates derived from 29 soil cores, over 300 forest inventory plots, water level, and elevation. The model included five mangrove tree species and was applied across seven regions around the Pacific Island of Pohnpei, Federated States of Micronesia, where mangrove forest is a critical ecosystem that supports subsistence living for local communities. We explored mangrove resilience and carbon accumulation under six sea-level rise scenarios. We also conducted an analysis to determine the sea-level rise rate threshold above which mangroves would be lost. The results suggest that Pohnpei mangroves can build their elevations relative to low and moderate rates of sea-level rise to prevent submergence, with limited loss of mangrove area through 2150. Under higher sea-level rise rates, however, forest elevation decreased substantially relative to mean sea level and there was extensive loss of mangrove area by that year. Regarding mangrove community composition, for all sea-level rise scenarios, the model predicted a change to increasing relative abundance of flood tolerant species and decreasing relative abundance of high-elevation species, which started to being realized by 2100. Variation in sediment supply, water levels, and elevation capital led to differential vulnerability around the island. We identified a threshold for Pohnpei mangroves where if local sea-level rise rates exceed 7.8 ± 2.2 mm/year they are projected to eventually submerge and be lost. Our modeling framework is novel by addressing both species interactions and critical belowground processes to better understand potential tidal ecosystem responses to sea-level rise.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-024-01422-y","usgsCitation":"Buffington, K., Carr, J., Mackenzie, R., Apwong, M., Krauss, K., and Thorne, K., 2024, Projecting mangrove forest resilience to sea-level rise on a Pacific Island: Species dynamics and ecological thresholds: Estuaries and Coasts, v. 47, p. 2174-2189, https://doi.org/10.1007/s12237-024-01422-y.","productDescription":"17 p.","startPage":"2174","endPage":"2189","ipdsId":"IP-165799","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":464362,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Federated States of Micronesia","otherGeospatial":"Pohnpei","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 158.07984414004875,\n 7.009358068074874\n ],\n [\n 158.07984414004875,\n 6.766699284998481\n ],\n [\n 158.36071659346305,\n 6.766699284998481\n ],\n [\n 158.36071659346305,\n 7.009358068074874\n ],\n [\n 158.07984414004875,\n 7.009358068074874\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"47","noUsgsAuthors":false,"publicationDate":"2024-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":918965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mackenzie, Richard","contributorId":264789,"corporation":false,"usgs":false,"family":"Mackenzie","given":"Richard","affiliations":[{"id":34924,"text":"U. Florida","active":true,"usgs":false}],"preferred":false,"id":918966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Apwong, Maybeleen","contributorId":251804,"corporation":false,"usgs":false,"family":"Apwong","given":"Maybeleen","email":"","affiliations":[{"id":25408,"text":"Institute of Pacific Islands Forestry, Pacific Southwest Research Station, Hilo, HI, USA","active":true,"usgs":false}],"preferred":true,"id":918967,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":223022,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":918968,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918969,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70262252,"text":"70262252 - 2024 - Long-term monitoring reveals management effects on Prairie Warbler colonization, local extinction, and detection in a Massachusetts pine barren","interactions":[],"lastModifiedDate":"2025-01-16T16:46:16.973077","indexId":"70262252","displayToPublicDate":"2024-10-04T10:43:01","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Long-term monitoring reveals management effects on Prairie Warbler colonization, local extinction, and detection in a Massachusetts pine barren","docAbstract":"Habitat management can directly impact Setophaga discolor (Prairie Warbler) abundance and distribution. Despite regional declines, Prairie Warbler populations at Camp Edwards (Bourne, MA) have increased. To investigate habitat-management effects on Prairie Warbler populations at Camp Edwards, we used a dynamic-occupancy model to analyze a long-term monitoring dataset collected across 84 point-count sites from 2013 to 2022. The model results indicated that Prairie Warbler colonization and extinction probabilities were impacted by management (measured in years since disturbance). Colonization probability was highest initially after disturbance, then subsequently decreased for ∼50 years, and extinction probability also decreased for ∼25 years. Both probabilities remained low before increasing at ∼75 years since disturbance. The increase in colonization probability >75 years since disturbance may have been an artifact of our study design and incomplete disturbance records. We also found that latitude and longitude significantly affected colonization probability, likely a result of how habitat types are distributed across the base. These results inform how Prairie Warblers respond to long-term management, suggesting that habitat management could improve colonization rates and sustain Prairie Warbler populations.
","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/045.031.0315","usgsCitation":"Gordon, A., Drummey, D., Tur, A., Curtis, A., McCumber, J., Akresh, M., and DiRenzo, G.V., 2024, Long-term monitoring reveals management effects on Prairie Warbler colonization, local extinction, and detection in a Massachusetts pine barren: Northeastern Naturalist, v. 31, no. 3, p. 418-434, https://doi.org/10.1656/045.031.0315.","productDescription":"17 p.","startPage":"418","endPage":"434","ipdsId":"IP-159827","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.6,\n 41.77\n ],\n [\n -70.6,\n 41.64\n ],\n [\n -70.5,\n 41.64\n ],\n [\n -70.5,\n 41.77\n ],\n [\n -70.6,\n 41.77\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"31","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gordon, Andrew B. Jr.","contributorId":348604,"corporation":false,"usgs":false,"family":"Gordon","given":"Andrew B.","suffix":"Jr.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":923651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drummey, Donovan","contributorId":348607,"corporation":false,"usgs":false,"family":"Drummey","given":"Donovan","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":923652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tur, Anthony","contributorId":348610,"corporation":false,"usgs":false,"family":"Tur","given":"Anthony","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":923653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Curtis, Annie E.","contributorId":348613,"corporation":false,"usgs":false,"family":"Curtis","given":"Annie E.","affiliations":[{"id":81976,"text":"Massachusetts Army National Guard","active":true,"usgs":false}],"preferred":false,"id":923654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCumber, Jacob C.","contributorId":348616,"corporation":false,"usgs":false,"family":"McCumber","given":"Jacob C.","affiliations":[{"id":81976,"text":"Massachusetts Army National Guard","active":true,"usgs":false}],"preferred":false,"id":923655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Akresh, Michael E.","contributorId":348619,"corporation":false,"usgs":false,"family":"Akresh","given":"Michael E.","affiliations":[{"id":83385,"text":"Antioch University","active":true,"usgs":false}],"preferred":false,"id":923656,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":923657,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70259166,"text":"sir20245062M - 2024 - Special topic—Rapid-response instrumentation","interactions":[{"subject":{"id":70259166,"text":"sir20245062M - 2024 - Special topic—Rapid-response instrumentation","indexId":"sir20245062M","publicationYear":"2024","noYear":false,"chapter":"M","displayTitle":"Special Topic—Rapid-Response Instrumentation","title":"Special topic—Rapid-response instrumentation"},"predicate":"IS_PART_OF","object":{"id":70259167,"text":"sir20245062 - 2024 - Recommended capabilities and instrumentation for volcano monitoring in the United States","indexId":"sir20245062","publicationYear":"2024","noYear":false,"title":"Recommended capabilities and instrumentation for volcano monitoring in the United States"},"id":1}],"isPartOf":{"id":70259167,"text":"sir20245062 - 2024 - Recommended capabilities and instrumentation for volcano monitoring in the United States","indexId":"sir20245062","publicationYear":"2024","noYear":false,"title":"Recommended capabilities and instrumentation for volcano monitoring in the United States"},"lastModifiedDate":"2024-10-17T20:45:04.668726","indexId":"sir20245062M","displayToPublicDate":"2024-10-04T10:30:24","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5062","chapter":"M","displayTitle":"Special Topic—Rapid-Response Instrumentation","title":"Special topic—Rapid-response instrumentation","docAbstract":"Based on the reports of Ewert and others (2005, 2018) and Moran and others (2008), most U.S. volcanoes are currently under-monitored and are likely to remain so until the goals of the National Volcano Early Warning System are fulfilled. In addition, volcanoes determined to have low to moderate threat levels (Ewert and others 2005, 2018) could awaken suddenly and, as a result, may need to have instrumentation installed rapidly. For these reasons, equipment caches would ideally be readily available for rapid response in the event of unrest at under-monitored volcanoes or during a volcanic crisis. Given that volcanoes in Alaska and Hawai‘i are frequently active, it is likely that several U.S. volcanoes could experience unrest simultaneously, as happened in 2018, 2019, and 2020, when unrest or eruptions occurred at Great Sitkin Volcano, Alaska; Mauna Loa, Hawai‘i; Mount Cleveland, Alaska; Semisopochnoi Island, Alaska; Shishaldin Volcano, Alaska; Mount Veniaminof, Alaska, as well as the most destructive documented eruption of Kīlauea, Hawai‘i. Therefore, we recommend that sufficient numbers of seismometers, infrasound sensors, Global Navigation Satellite System (GNSS) receivers, remote cameras, gas-monitoring instruments, and airborne and ground-based remote-sensing systems be made available and placed in a state of readiness at each observatory with the capability of bringing a level-2 monitoring network to near level-4 readiness. These rapid-response caches would ideally include sufficient equipment to provide real-time data telemetry, including satellite telemetry, where available, applicable, and appropriate. Rapid-response caches would be maintained in a state of readiness so that instruments can be deployed within several hours to days. Although the primary focus of the caches would be to enable rapid increases to a volcano observatory’s real-time monitoring capabilities, not all scenarios of volcanic unrest are conducive to rapid deployment of real-time data telemetry. Non-telemetered, campaign instruments, particularly seismometers and GNSS stations, can also be deployed to aid in detection of early signs of volcanic unrest given the data can be recovered in a timely fashion.
Given the geographic separation of the U.S. Geological Survey Volcano Science Center’s (VSC) four volcano observatory offices, the logistical difficulties in shipping equipment rapidly between them in response to unrest, the possible scenario that a volcano could reawaken with just hours or days of precursory unrest, and the difference in operating environments (for example, tropical Hawai‘i compared to subarctic Alaska), we recommend three rapid-response instrument caches—for Hawai‘i, Alaska, and the lower 48 States. For the lower 48 States, a single cache shared among the Cascades Volcano Observatory, Yellowstone Volcano Observatory, and the California Volcano Observatory could be warehoused in California or Washington. Although these rapid-response caches would be located at one of the observatories, they would ideally be owned and maintained by VSC, and together form a flexible VSC-wide instrument pool. To maintain continuity of monitoring capabilities, this rapid-response cache could also serve to replace instruments destroyed during an on-going eruption. However, to retain eruption-response readiness, we recommend instruments in the rapid-response cache not be permanently reallocated to an observatory’s monitoring network unless they are replaced.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245062M","usgsCitation":"Flinders, A.F., 2024, Special topic—Rapid-response instrumentation, chap. M of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–M, 4 p., https://doi.org/10.3133/sir20245062M.","productDescription":"iii, 4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-153111","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":462409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5062/m/covrthbm.jpg"},{"id":462410,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5062/m/sir20245062m.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"Director,
Volcano Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, AK 99508
Unoccupied aircraft systems (UAS) increasingly support volcano monitoring and eruption response activities in the United States and abroad (James and others, 2020). Advances in UAS platforms and miniaturization of sensors over the past decade have expanded the use of this technology for a wide range of applications within volcanology (Jordan, 2019; James and others, 2020). UAS can greatly enhance existing ground-, aerial-, and satellite-based observation and in situ monitoring networks at volcanoes by providing new avenues for data collection in terms of access, resolution, and timing. UAS can collect data in difficult and hazardous environments, reducing risk to occupied aircraft and (or) ground crews; support the generation of dense time series of data through frequent, low-cost, high-resolution surveys; and provide real-time, on-demand measurements at volcanic systems for indicators such as gas, thermal output, and topographic change without the need to wait for contracted aerial flight services or satellite orbit intervals.
During the 2018 response to the Kīlauea eruption on the Island of Hawaiʻi, UAS were used extensively and successfully to monitor, track, investigate, and (or) warn of ongoing volcanic activity (fig. L1; Neal and others, 2019). Throughout the eruption, the UAS team was able to provide data products rapidly to emergency managers for situational awareness and to scientists for quantitative hazard assessment (Diefenbach and others, 2018). Over the course of 4 months, more than 1,200 UAS missions were flown and yielded critical data that included (1) live video to emergency operations centers in Hilo and Honolulu for situational awareness; (2) gas emission rates, compositions, and concentrations; (3) repeat nadir videos over sections of the lava channel to support measurements of lava effusion rate; (4) oblique videos for hazards assessment and outreach; and (5) photogrammetry surveys to create very high-resolution topographic models and orthophoto mosaics (Diefenbach and others, 2018). In coming years, the U.S. Geological Survey (USGS) Volcano Hazards Program (VHP) plans to expand its fleet of UAS, associated sensors, and remote pilots to enhance volcano monitoring and response capabilities.
Currently (2023), USGS operational capabilities are restricted to small class UAS (sUAS; less than [<] 55 pounds) that are limited in range, payload capacity, and flight duration. Additionally, USGS-piloted platforms are restricted to the U.S. Department of the Interior Office of Aviation Services approved fleet, which includes a limited number of small and medium multi-rotor aircraft and vertical take-off and landing fixed-wing aircraft (https://www.doi.gov/aviation/uas/fleet). Each type of platform has advantages and disadvantages. Small rotor-wing quadcopters are fast to deploy, can be carried in a backpack, and are highly maneuverable, but are typically only equipped with a small camera and have a minimal flight range. Medium rotor-wing hexacopters can carry larger payloads (< 20 kilograms [kg]) and varied sensors, but, with the drawback of minimal flight time (<30 minutes), they typically have similar range capabilities to their smaller counterparts and are not as easily deployable. Fixed-wing platforms provide relatively long endurance (<60 minutes) and range and, with the vertical take-off and landing capabilities, can launch and land in relatively small spaces; however, they have less maneuverability and hovering capability than the rotor-wing platforms. Although the 2018 Kīlauea response showed the benefit of the current UAS fleet, all platforms have limited range [<10 kilometers (km)], such that operators must be stationed relatively close to the region of interest. To expand UAS monitoring capabilities, VHP staff have been working closely with industry partners and the National Aeronautics and Space Administration to develop a next-generation UAS for volcano monitoring (Kern and others, 2020). This ruggedized, mid-range (>20 km), multiparametric (gas and photogrammetry) UAS has been developed to meet volcano monitoring needs, particularly at less accessible, more dangerous stratovolcanoes. It is expected in the coming years that additional UAS platforms with new and smaller sensors will expand our capabilities to meet the Nation’s volcano monitoring objectives.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245062L","usgsCitation":"Diefenbach, A.K., 2024, Special topic—Unoccupied aircraft systems, chap. L of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–L, 5 p., https://doi.org/10.3133/sir20245062L.","productDescription":"iii, 5 p.","numberOfPages":"5","onlineOnly":"N","ipdsId":"IP-149693","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":462411,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5062/l/covrthbl.jpg"},{"id":462412,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5062/l/sir20245062l.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"Director,
Volcano Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, AK 99508
Explosive eruptions create plumes of volcanic ash and gas that can rise more than 30,000 feet (9.1 kilometers [km]) above sea level within minutes of eruption onset. The resulting clouds disperse under prevailing winds and may cause hazardous conditions hundreds to thousands of kilometers from the volcano, including in international airspace. Rapid detection and characterization of explosive activity is vital to mitigate the wide-ranging effects of volcanic ash. Ashfall thicknesses as small as a millimeter or so on the ground can affect infrastructure, agriculture, and air quality, requiring extensive clean-up procedures (Schuster, 1981; Warrick and others, 1981, U.S. Geological Survey, 2022). Volcanic clouds also pose substantial threats to aircraft. Since 1953, 88 encounters between airplanes and ash clouds have been documented worldwide (International Civil Aviation Organization, 2015, appendix F), resulting in aircraft damage and, in 9 cases, engine failure (Guffanti and others, 2010). In 1982, two large passenger planes suffered complete engine failure owing to eruptions in Indonesia (Global Volcanism Program, 1982) and a similar incident occurred over Alaska in 1989 (Casadevall, 1994). In all three cases, they were able to restart some engine capability and land safely once they emerged from the ash clouds, although with substantial damage (Guffanti and others, 2010).
The clear threat to aviation has led to establishment of nine Volcanic Ash Advisory Centers (VAAC) around the world to monitor and rapidly disseminate information about volcanic eruptions to the aviation community. U.S. Geological Survey (USGS) volcano observatories issue the Volcano Observatory Notice for Aviation that informs of preeruptive unrest or eruptive activity. When ash-producing eruptions do occur, volcano observatories work closely with their regional VAAC to ensure consistency and accuracy in eruption onset time, cloud altitude, ash production, and duration as reported in Volcanic Ash Advisories. Explosive volcanism in the United States and Commonwealth of the Northern Mariana Islands prompts 50–100 such advisories in any given year (table J1). This collaborative effort is greatly aided by USGS detection and monitoring of eruption clouds to ensure a timely and coordinated response.
To support these efforts to provide guidance on ash transport and fallout, the USGS developed the Ash3d volcanic ash dispersion model (https://vsc-ash.wr.usgs.gov/ash3d-gui) (Schwaiger and others, 2012). Automated simulations are run daily by the USGS for volcanoes that are in elevated states of unrest, and in response mode when eruptions occur. During eruptions, the model output is provided to local National Weather Service Weather Forecast Offices to guide them in the issuance of their information products (such as special weather statements, ashfall advisories, or ashfall warnings), as well as to State and local governments and the public. Characterization of the eruption source is needed to estimate the parameters used to initialize the Ash3d model, and by the Anchorage and Washington VAACs to initialize other dispersion models that inform forecasts for the airborne volcanic cloud. The source parameters that can be provided by observation during an eruption include eruption start time, eruption cloud height over time, and eruption duration. Other, nonobservable source parameters, such as mass eruption rate and grain-size distribution, are based on empirical correlations and study of historical deposits. The goal is to provide a time series of cloud heights, mass eruption rates, and particle-size distributions that accurately reflects current conditions. When feasible, the USGS also provides guidance on the nature of ongoing eruptions and forecasts future activity using petrologic monitoring of collected tephra samples.
The aims of providing accurate observable parameters are achieved through analysis of (1) near-real-time meteorological satellite data, (2) ground-based cameras (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–G, 11 p., https://doi.org/10.3133/sir20245062g.\">chapter G, this volume; Orr and others, 2024), (3) weather radar, (4) volcanic lightning detection, and (5) ground-based ash sensors and sampling. Explosive eruptions can be detected by a variety of geophysical monitoring, including infrasound (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–C, 11 p., https://doi.org/10.3133/sir20245062c.\">chapter C, this volume; Lyons and others, 2024) and seismicity (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–B, 9 p., https://doi.org/10.3133/sir20245062b.\">chapter B, this volume; Thelen and others, 2024). However, those methods cannot quantify the altitude, ash content, and dispersal dynamics of resulting volcanic clouds. Ideally, all available sources of monitoring data are synthesized to develop a coherent understanding of eruptive activity. The guidance summarized here provides a framework for characterizing volcanic clouds in the atmosphere and tracking the evolution of explosive eruption dynamics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245062J","usgsCitation":"Schneider, D.J., and Van Eaton, A.R., 2024, Special topic—Eruption plumes and clouds, chap. J of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–J, 12 p., https://doi.org/10.3133/sir20245062J.","productDescription":"iii, 12 p.","numberOfPages":"12","onlineOnly":"N","ipdsId":"IP-154938","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":462415,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5062/j/covrthbj.jpg"},{"id":462416,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5062/j/sir20245062j.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"Director,
Volcano Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, AK 99508
Submarine volcanoes produce much of the same seismicity and eruptive activity as subaerial volcanoes and can pose hazards to society. Although they can be monitored with similar techniques and methods as described in other chapters of this volume, their submerged location brings unique challenges. This chapter addresses these challenges and provides recommendations for monitoring volcanoes fully or partly in marine environments to meet the capabilities described in other chapters of this volume.
The United States and its territories host dozens of submarine volcanoes with most (around 60) in the Commonwealth of the Northern Mariana Islands. Approximately 20 of the Northern Mariana Islands submarine volcanoes are known to be hydrothermally active, and 10 have confirmed eruptions since the 1950s (for example, Baker and others, 2008; Tepp and others, 2019a). Nine of those volcanoes were considered by the National Volcanic Threat Assessment (Ewert and others, 2018) to have a combination of eruptive type and summit depth that poses a higher risk of hazardous eruptions, although only one was listed as a moderate (level 3) threat. Other notable submarine volcanoes of interest to the United States that have historically erupted are Axial Seamount off the Washington State coast, Kamaʻehuakanaloa in Hawaiʻi, and Vailuluʻu seamount in American Samoa. All of these, however, have a low risk of hazards because of their depth (greater than 600 meters below sea level) and eruptive type and so are not included in the National Volcanic Threat Assessment. In addition to submarine volcanoes, the submerged flanks of island volcanoes can also be a source of hazardous submarine eruptions—for example, the 1877 eruption of Mauna Loa, Hawai‘i, in Kealakekua Bay (Wanless and others, 2006).
The most notable submarine eruption in recent times was the 2022 eruption of Hunga Tonga–Hunga Haʻapai in Tonga, which was one of the largest eruptions on Earth in the past 100 years. It created a massive volcanic plume, unprecedented shock waves, and far-reaching tsunami (Lynett and others, 2022). Other recent submarine eruptions in the Pacific Ocean Basin have produced subaerial plumes that reached aircraft heights (Carey and others, 2014) and large pumice rafts that can affect marine traffic and harbors (for example, Jutzeler and others, 2014; Kornei, 2019). These examples illustrate the potential hazards of major submarine eruptions. Yet, submarine volcanoes are largely unmonitored, and many eruptions occur that are unnoticed or only identified hours or days afterward.
Within U.S. territory, submarine volcanoes in the Northern Mariana Islands have been known to produce eruptive activity that can affect society. Reports from fishermen and other marine vessels in the Northern Mariana Islands have noted underwater explosions, sea-surface discoloration, and bubbling water, all of which are known to be signs of submarine volcanic activity. South Sarigan seamount, located about 160 kilometers (km) north of Saipan, erupted in 2010 from greater than 150 meters below the sea surface, resulting in a gas and ash plume that reached more than 11.9 km into the atmosphere (for example, Searcy, 2013; Embley and others, 2014), high enough to affect international air traffic. Precursory and co-eruptive seismicity was detected on the regional Northern Mariana Islands seismic network (Searcy, 2013) and on global monitoring instruments (Green and others, 2013).
Monitoring of submarine volcanoes is best accomplished with marine-based instrumentation, which is also useful for monitoring small island volcanoes that may not have the land area necessary for comprehensive subaerial monitoring. The primary marine-based instrumentation used for submarine volcanoes includes ocean-bottom pressure sensors to assess sea-floor deformation, ocean-bottom seismometers (OBSs) to detect seismicity, and both moored and ocean-bottom hydrophones to detect submarine explosions. Other sensors offer important monitoring data, such as turbidity, temperature, and chemistry of hydrothermal emissions. Marine-based instruments are typically deployed in campaign-style networks with no real-time telemetry owing to cost considerations and technical limitations. However, when necessary, marine instruments can be operated in real time using cables to transmit data to land-based facilities; other technologies for this purpose are in use or in development, such as acoustic transmission from the instrument to a moored buoy (Matsumoto and others, 2016) and a winch-based system with a satellite antenna that is part of the instrument mooring (Matsumoto and others, 2019). Emerging technologies for marine-based monitoring may be considered as part of a future monitoring plan. These technologies include ocean gliders and floats with on-board hydrophones that have been used to record earthquakes and submarine eruptions (for example, Matsumoto and others, 2013; Sukhovich and others, 2015) and fiber-optic cables that have been used as strainmeters to detect earthquakes (for example, Marra and others, 2018; Lindsey and others, 2019). Land-based instruments and satellites can also provide some capability for monitoring submarine volcanoes, but they provide more limited observations than marine-based instrumentation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245062I","usgsCitation":"Tepp, G., 2024, Monitoring marine eruptions, chap. I of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–I, 7 p., https://doi.org/10.3133/sir20245062I.","productDescription":"iii, 7 p.","numberOfPages":"7","onlineOnly":"N","ipdsId":"IP-149126","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":462443,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5062/i/covrthbi.jpg"},{"id":462444,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5062/i/sir20245062i.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"Director,
Volcano Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, AK 99508
When magma accumulates or migrates, it can cause pressurization and related ground deformation. Characterization of surface deformation provides important constraints on the potential for future volcanic activity, especially in combination with seismic activity, gas emissions, and other indicators. A wide variety of techniques and instrument types have been applied to the study of ground deformation at volcanoes (sidebar, p. 2; Dzurisin, 2000, 2003, 2007). Geodetic instruments include continuously recording Global Navigation Satellite System (GNSS; of which the United States’ Global Positioning System is one example) stations (fig. D1), borehole tiltmeters, and interferometric synthetic aperture radar (InSAR) measurements (from satellites, occupied and unoccupied aircraft systems, and ground-based sensors). Additional geodetic measurements like continuous- and survey-mode gravity (fig. D2) can contribute substantially to interpreting these data. Borehole strainmeters (see chapter K, this volume, by Hurwitz and Lowenstern, 2024) also have outstanding utility for monitoring deformation, although because of cost and permitting challenges, we do not include them as part of standard volcano monitoring networks for U.S. volcanoes. Still other techniques like light detection and ranging (lidar), structure from motion, and optical satellite data can be used to derive gross topographic changes, which can be used to map volcanic deposits, infer eruption rates, and gain insights into the source processes associated with eruptive activity (see chapter G, this volume, on tracking surface changes caused by volcanic activity; Orr and others, 2024).
Experience has shown that no single geodetic monitoring technique is adequate to detect and track the entire range of ground-motion patterns that occur at volcanoes, primarily because of the temporal and spatial diversity of volcano deformation (fig. D3). Similarly, the magnitude of surface deformation varies widely. Geodetic monitoring strategies should therefore include multiple techniques and instrument types to cover a wide range of spatial and temporal scales.
In identifying recommendations for geodetic instrumentation for volcano monitoring networks, we attempted to maximize the diversity of instrument types to measure the full range of deformation signals and minimize their expense and number; thus, we do not include several well-known deformation-monitoring techniques in our recommendations. Extensometers, for example, measure strains over distances of a few meters and have an excellent record of success in detecting changes in preeruptive localized ground motion across existing cracks, including at Mount St. Helens, Washington (Iwatsubo and others, 1992), and Piton de la Fournaise, Réunion Island (Peltier and others, 2006). Despite being relatively inexpensive, extensometers are best used primarily when localized ground displacements (for example, ground cracks) need to be tracked, and are not necessary at all volcanoes.
In considering volcano deformation monitoring strategies, two complicating factors are deserving of special attention. First, not all deformation is driven by subsurface magmatic activity—for example, at many large stratovolcanoes (for example, Mount Rainier), flank collapses and landslides are significant geologic hazards (Reid and others, 2001) that may occur even in the absence of magmatic activity. Monitoring the stability of volcanoes is thus another critical application of geodetic monitoring networks to inform hazard assessment. One of the most famous examples of edifice instability is the large flank collapse that initiated the May 18, 1980, eruption of Mount St. Helens. Deformation monitoring had detected a bulge on the north flank of the mountain in April 1980 that was expanding by several meters per day (Lipman and others, 1981). Given that flank collapses can happen at any time during a period of volcanic unrest (or even outside a period of unrest), the capability to assess edifice stability is critical.
Second, although volcanoes are commonly treated as idealized structures that erupt from single points, like centralvent stratovolcanoes, many are characterized by long rift zones from which eruptions may originate, and distributed volcanic fields are characterized by broadly spaced vents. For example, linear dikes are common at Kīlauea, Mauna Loa, and between Mount Shasta and Medicine Lake in California. At Kīlauea, one of these linear dikes emerged more than 40 kilometers (km) away from the summit of the volcano during the lower East Rift Zone eruption in 2018. Other volcanic fields, like Lassen volcanic center, California, or the San Francisco Volcanic Field, Arizona, have many small vents spread over a wide area. Although the instrumentation guidelines presented in this chapter remain phrased for central-vent volcanoes, they should be modified as needed in the context of the eruptive characteristics of each individual volcanic system.
Spatial analysis of geodetic network coverage could help to ensure adequate instrumentation in areas where volcanism can occur over a broad area as opposed to a central vent. As an example, consider the adjacent volcanoes Mount Shasta and Medicine Lake. If station locations are chosen based only on the distance from the centers of the volcanoes, then any geodetic anomalies between the two volcanoes—an area of potential volcanism as indicated by the presence of volcanic features—may remain undetected by ground-based instrumentation. The spatial analysis is accomplished via a grid of pressure point sources (Mogi, 1958) evenly distributed across the map area, at a depth of 5 km in this example (fig. D4). Each source is inflated until predicted deformations exceed the GNSS white noise uncertainty estimates at one site (Langbein, 2017; Murray and Svarc, 2017). This volume of detectable magma provides a measure of the quality of the coverage (fig. D4). The results indicate that, as of 2022, there is a large area between Mount Shasta and Medicine Lake volcano with existing mapped dikes in which a substantial amount of magma could intrude without being detected geodetically. Applying this style of analysis to individual volcanic systems can provide a guide for designing network geometry given the expected locations of future eruptions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245062D","usgsCitation":"Montgomery-Brown, E.K., Anderson, K.R., Johanson, I.A., Poland, M.P., and Flinders, A.F., 2024, Ground deformation and gravity for volcano monitoring, chap. D of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–D, 11 p., https://doi.org/10.3133/sir20245062D.","productDescription":"iv, 11 p.","numberOfPages":"11","onlineOnly":"N","ipdsId":"IP-152739","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":462454,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5062/d/sir20245062d.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":462453,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5062/d/covrthbd.jpg"}],"contact":"Director,
Volcano Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, AK 99508
Translocating amphibians to alternative, suitable habitat is a climate adaptation strategy aimed at minimizing the risk of extinction due to projected global warming and drying. Projected conditions could undermine their physiological performance, and thus survival and reproduction. Translocations minimize risks of extinction by increasing spatial redundancy across climate-resilient habitats, particularly for dispersal-limited species. However, outcomes of amphibian translocation attempts are poorly documented, and their effectiveness remains unclear. We released and tracked 34 Eleutherodactylus coqui to determine early postrelease survival of a control (nontranslocated) group (n = 14) and experimental (translocated) group (n = 20) moved 0.8 km from their capture location in west-central Puerto Rico in 2021. We defined “initial” as the first 17 d postrelease, a period during which we hypothesized that experimental individuals would have lower survival rates because they transitioned from known-familiar to novel-unfamiliar habitat. We found no evidence in the data to support our hypothesis. Daily survival rates were better explained by a model with no group effect but negatively influenced by in situ temperature. However, the effect of in situ temperature (proxy of operative temperature) was weak (95% confidence intervals overlapped 0). After 17 d, all but one of the recaptured frogs lost weight for a combined weight loss of 0.28 ± 0.13 g. However, weight loss was significantly higher in translocated frogs (0.81 ± 0.33 g). Average daily movements did not hinder survival even though experimental individuals traveled farther (～ eight times) than control ones. Our findings suggested that managed translocations have the potential to become a useful conservation tool, not an additive source of mortality. We outline challenges that remain before translocations of Eleutherodactylus species can be broadly applied.
","language":"English","publisher":"BioOne","doi":"10.1655/Herpetologica-D-24-00001.1","usgsCitation":"Chaparro, R., Rivera-Burgos, A., Eaton, M.J., Terando, A., Martinez, E., and Collazo, J.A., 2024, Postrelease survival of Eleutherodactylus coqui: Advancing managed translocations as an adaptive tool for climate-vulnerable anurans: Herpetologica, v. 80, no. 4, p. 314-320, https://doi.org/10.1655/Herpetologica-D-24-00001.1.","productDescription":"7 p.","startPage":"314","endPage":"320","ipdsId":"IP-157773","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":487927,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1655/herpetologica-d-24-00001.1","text":"Publisher Index Page"},{"id":485331,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.02528621431577,\n 18.25\n ],\n [\n -67.02528621431577,\n 18.086320441291832\n ],\n [\n -66.90560779954839,\n 18.086320441291832\n ],\n [\n -66.90560779954839,\n 18.25\n ],\n [\n -67.02528621431577,\n 18.25\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"80","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Chaparro, Rafael","contributorId":354406,"corporation":false,"usgs":false,"family":"Chaparro","given":"Rafael","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":935586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rivera-Burgos, Ana C.","contributorId":354407,"corporation":false,"usgs":false,"family":"Rivera-Burgos","given":"Ana C.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":935587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":935588,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Terando, Adam 0000-0002-9280-043X","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":205908,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":935589,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martinez, Eloy","contributorId":354408,"corporation":false,"usgs":false,"family":"Martinez","given":"Eloy","affiliations":[{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false}],"preferred":false,"id":935590,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Collazo, Jaime A. 0000-0002-1816-7744","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":217287,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime","email":"","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":935591,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70259395,"text":"70259395 - 2024 - Arctic fishes reveal patterns in radiocarbon age across habitats and with recent climate change","interactions":[],"lastModifiedDate":"2024-11-22T16:13:19.150412","indexId":"70259395","displayToPublicDate":"2024-10-04T06:30:46","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5456,"text":"Limnology and Oceanography Letters","active":true,"publicationSubtype":{"id":10}},"title":"Arctic fishes reveal patterns in radiocarbon age across habitats and with recent climate change","docAbstract":"Climate change alters the sources and age of carbon in Arctic food webs by fostering the release of older carbon from degrading permafrost. Radiocarbon (14C) traces carbon sources and age, but data before rapid warming are rare and limit assessments over time. We capitalized on 14C data collected ~ 40 years ago that used fish as natural samplers by resampling the same species today. Among resampled fish, those using freshwater food webs had the oldest 14C ages (> 1000 yr BP), while those using marine food webs had the youngest 14C ages (near modern). One migratory species encompassed the entire range of 14C ages because juveniles fed in freshwater streams and adults fed in offshore marine habitats. Over ~ 40 yr, average 14C ages of freshwater and marine feeding fish shifted closer to atmospheric values, suggesting a potential influence from “greening of the Arctic.”