Mercury is a widespread, naturally occurring contaminant that biomagnifies in wetlands due to the methylation of this element by sulfate-reducing bacteria. Species that feed at the top trophic level within wetlands are predicted to have higher mercury loads compared to species feeding at lower trophic levels and are therefore often used for mercury biomonitoring. However, mechanisms for mercury bioaccumulation in sentinel species are often poorly understood, due to a lack of long-term studies or an inability to differentiate between confounding variables. We examined mercury bioaccumulation patterns in the whole blood of American alligators (Alligator mississippiensis) from a long-term mark-recapture study (1979–2017) in South Carolina, USA. Using a growth model and auxiliary information on predicted age at first capture, we differentiated between age- and size-related variation in mercury bioaccumulation, which are often confounded in alligators due to their determinate growth pattern. Contrary to predictions that the oldest or largest individuals were likely to have the highest mercury concentrations, our best-supported model indicated a peak in mercury concentration at 30–40 years of age, depending on the sex, and lower concentrations in the youngest and oldest animals. To evaluate the robustness of our findings, we re-analyzed data from a previously published study of mercury in alligators sampled at Merritt Island National Wildlife Refuge in Florida. Unlike the South Carolina data, the data from Florida contained minimal auxiliary information regarding age, yet the best supported model similarly indicated a peaked rather than increasing relationship between mercury and body size, a less-precise indicator of age. These findings highlight how long-term monitoring can differentiate between confounding variables (e.g., age and size) to better elucidate complex relationships between contaminant exposure and demographic factors in sentinel species.
We measure pseudospectral and peak ground motions from 44 intermediate‐depth
The 30 November 2018
Monitoring population performance in the years following species reintroductions is key to assessing population restoration success and evaluating assumptions made in planning species restoration programs. From 2008–2010 we translocated 90 fishers (Pekania pennanti) from British Columbia, Canada, to Washington's Olympic Peninsula, USA, providing the opportunity to evaluate modeling assumptions used to identify the most suitable reintroduction areas in Washington and enhance understanding of fisher habitat associations in the late‐successional forest ecosystems in the coastal Pacific Northwest. From 2013–2016, we deployed 788 motion‐sensing cameras and hair (DNA)‐snaring devices distributed among 263 24‐km2 primary sampling units across the Olympic Peninsula. Our objectives were to determine whether occupancy patterns of the reestablishing population supported assumptions of the initial habitat assessment models, whether the population had expanded or shifted in distribution since the initial reintroductions, compare physical habitat attributes among land‐management designations, and determine whether the founding fishers had successfully reproduced. We predicted that site occupancy by fishers would be associated with landscapes characterized by high proportional coverage of dense forest canopies and medium‐sized and large trees, a diversity of stand structural classes, and area near the administrative boundary separating wilderness from more intensively managed forest lands. We detected fishers across designated wilderness, federal lands outside of wilderness, and other land designations in proportion to land availability on the Peninsula. We found negligible support for predictions that occupancy by fishers was associated with percent forest cover, tree‐size class, or structural class diversity. Rather, occupancy was strongly associated with lands near the wilderness boundary on both sides. We speculate that the boundary between wilderness and more intensively managed forest lands provided fishers with the most suitable prey in proximity to contiguous expanses of low‐ to mid‐elevation late‐successional forests that provided optimal resting, denning, and security values. Occupancy patterns shifted toward the west and south along a precipitation gradient during the study, indicating that population distribution had not yet stabilized 5–8 years following translocation. Genetic results indicated that ≥2 generations of fishers have been produced on the Peninsula. Annual occupancy rates across the Peninsula (0.08–0.24) were lower than in other previously studied and established fisher populations, indicating that not all habitat was fully occupied or that initial estimates of the extent of habitat was overestimated. The strong selection fishers exhibited for wilderness edge and weak selection against extensive forested wilderness areas suggested that habitat managers should strive for maintaining a suitable interspersion of required forest structures and biotic habitat components, such as prey resource availability.
Fog and low cloud cover (FLCC) and late summer recharge increase stream baseflow and decrease stream temperature during arid Mediterranean climate summers, which benefits salmon especially under climate warming conditions. The potential to discharge cool water to streams during the late summer (hydrologic capacity; HC) furnished by FLCC and recharge were mapped for the 299 subwatersheds ranked Core, Phase 1, or Phase 2 under the National Marine Fisheries Service Recovery Plan that prioritized restoration and threat abatement action for endangered Central California Coast Coho Salmon evolutionarily significant unit. Two spatially continuous gridded datasets were merged to compare HC: average hrs/day FLCC, a new dataset derived from a decade of hourly National Weather Satellite data, and annual average mm recharge from the USGS Basin Characterization Model. Two use‐case scenarios provide examples of incorporating FLCC‐driven HC indices into long‐term recovery planning. The first, a thermal analysis under future climate, projected 65% of the watershed area for 8–19 coho population units as thermally inhospitable under two global climate models and identified several units with high resilience (high HC under the range of projected warming conditions). The second use case investigated HC by subwatershed rank and coho population, and identified three population units with high HC in areas ranked Phase 1 and 2 and low HC in Core. Recovery planning for cold‐water fish species would benefit by including FLCC in vulnerability analyses.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12811","usgsCitation":"Torregrosa, A.A., Flint, L.E., and Flint, A.L., 2020, Hydrologic resilience from summertime fog and recharge: A case study for coho salmon recovery planning: Journal of the American Water Resources Association, v. 56, no. 1, p. 134-160, https://doi.org/10.1111/1752-1688.12811.","productDescription":"27 p.","startPage":"134","endPage":"160","ipdsId":"IP-095384","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":458480,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12811","text":"Publisher Index Page"},{"id":372761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.18945312500001,\n 41.96765920367816\n ],\n [\n -128.0126953125,\n 38.39333888832238\n ],\n [\n -122.9150390625,\n 34.08906131584994\n ],\n [\n -117.79541015625001,\n 36.82687474287728\n ],\n [\n -124.18945312500001,\n 41.96765920367816\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Torregrosa, Alicia A. 0000-0001-7361-2241 atorregrosa@usgs.gov","orcid":"https://orcid.org/0000-0001-7361-2241","contributorId":3471,"corporation":false,"usgs":true,"family":"Torregrosa","given":"Alicia","email":"atorregrosa@usgs.gov","middleInitial":"A.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":783455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783457,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216943,"text":"70216943 - 2020 - Could a freshwater fish be at the root of dystrophic crises in a coastal lagoon?","interactions":[],"lastModifiedDate":"2020-12-17T14:06:31.950476","indexId":"70216943","displayToPublicDate":"2019-11-20T07:52:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Could a freshwater fish be at the root of dystrophic crises in a coastal lagoon?","docAbstract":"Eutrophication has a profound impact on ecosystems worldwide. Grass carp Ctenopharyngodon idella, an herbivorous fish, has been introduced to control aquatic plant overgrowth caused by eutrophication, but could have other, potentially detrimental, effects. We used the Po di Volano basin (south of the Po River delta, northern Italy) as a test case to explore whether grass carp effects on canal aquatic vegetation could be at the root of historical changes in N loads exported from the basin to the Goro Lagoon. We modeled the aquatic vegetation production and standing crop, its denitrification potential, and its consumption by introduced grass carp. We then examined whether changes in historical nitrogen loads matched the modeled losses of the drainage network denitrification function or other changes in agricultural practices. Our results indicate that introduced grass carp could completely remove submerged vegetation in the Po di Volano canal network, which could – in turn – lead to substantial loss of the denitrification function of the system, causing in an increase in downstream nitrogen loads. A corresponding increase, matching both timing and magnitude, was detected in historical nitrogen loads to the Goro Lagoon, which were significantly different before and after the time of modeled collapse of the denitrification function. This increase was not clearly linked to watershed use or agricultural practices, which implies that the loss of the denitrification function through grass carp overgrazing could be a likely explanation of the increase in downstream nitrogen loads. Perhaps for the first time, we provide evidence that a freshwater fish introduction could have caused long-lasting changes in nutrient dynamics that are exported downstream to areas where the fish is not present.
The multisegment Wasatch fault zone is a well-studied normal fault in the western United States that has paleoseismic evidence of recurrent Holocene surface-faulting earthquakes. Along the 270-km-long central part of the fault, four primary structural complexities provide possible along-strike limits to these ruptures and form the basis for models of fault segmentation. Here, we assess the impact that the Wasatch fault segmentation model has on seismic hazard by evaluating the time-independent long-term rate of ruptures on the fault that satisfy fault slip rates and paleoseismic event rates, adapting standard inverse theory used in the Uniform California Earthquake Rupture Forecast 3 (UCERF3), and implementing a segmentation constraint where ruptures across primary structural complexities are penalized. We define three models with varying degrees of rupture penalization: (1) segmented (ruptures confined to individual segments), (2) penalized (multi-segment ruptures allowed, but penalized), and (3) unsegmented (all ruptures allowed). Seismic-hazard results show that on average, hazard is highest for the segmented model, where seismic moment is accommodated by frequent moderate (moment magnitude, Mw 6.2–6.8) earthquakes. The unsegmented model yields the lowest average seismic hazard because part of the seismic moment is accommodated by large (Mw 6.9–7.9), but infrequent ruptures. We compare these results to model differences derived from other inputs such as slip rate and magnitude scaling relationships and conclude that segmentation exerts a primary control on seismic hazard. This study demonstrates the need for additional geologic constraints on rupture extent and methods by which these observations can be included in hazard-modeling efforts.
","language":"English","publisher":"GeoScienceWorld","doi":"10.1785/0120190088","usgsCitation":"Valentini, A., DuRoss, C., Field, E., Gold, R.D., Briggs, R.W., Visini, F., and Pace, B., 2020, Relaxing segmentation on the Wasatch Fault Zone: Impact on seismic hazard : Bulletin of the Seismological Society of America, v. 110, no. 1, p. 83-109, https://doi.org/10.1785/0120190088.","productDescription":"27 p.","startPage":"83","endPage":"109","ipdsId":"IP-111708","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":370502,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"110","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Valentini, Alessandro","contributorId":221390,"corporation":false,"usgs":false,"family":"Valentini","given":"Alessandro","email":"","affiliations":[{"id":40356,"text":"Università degli Studi “G. d’Annunzio” di Chieti-Pescara, InGeo Department","active":true,"usgs":false}],"preferred":false,"id":778013,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DuRoss, Christopher 0000-0002-6963-7451 cduross@usgs.gov","orcid":"https://orcid.org/0000-0002-6963-7451","contributorId":152321,"corporation":false,"usgs":true,"family":"DuRoss","given":"Christopher","email":"cduross@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":1165,"corporation":false,"usgs":true,"family":"Field","given":"Edward H.","email":"field@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":778019,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778016,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778018,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Visini, Francesco","contributorId":221392,"corporation":false,"usgs":false,"family":"Visini","given":"Francesco","email":"","affiliations":[{"id":40358,"text":"Istituto Nazionale di Geofisica e Vulcanologia, sezione di Pisa","active":true,"usgs":false}],"preferred":false,"id":778017,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pace, Bruno","contributorId":221391,"corporation":false,"usgs":false,"family":"Pace","given":"Bruno","email":"","affiliations":[{"id":40357,"text":"Università degli Studi “G. d’Annunzio” di Chieti-Pescara, DiSPUTer Department","active":true,"usgs":false}],"preferred":false,"id":778015,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70206961,"text":"70206961 - 2020 - Using integrated population models for insights into monitoring programs: An application using pink-footed geese","interactions":[],"lastModifiedDate":"2019-12-03T06:43:13","indexId":"70206961","displayToPublicDate":"2019-11-19T11:43:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Using integrated population models for insights into monitoring programs: An application using pink-footed geese","docAbstract":"Development of integrated population models (IPMs) assume the absence of systematic bias in monitoring programs, yet many potential sources of systematic bias in monitoring data exist (e.g., under-counts of abundance). By integrating multiple sources of data, we can assess whether various sources of monitoring data provide consistent inferences about changes in population size and, thus, whether monitoring programs appear unbiased. For the purposes of understanding how IPMs could provide insights for monitoring programs, we used the Svalbard breeding population of pink-footed goose (Anser brachyrhynchus) as a case study. The Svalbard pink-footed goose is a well-studied species, the focus of the first adaptive-harvest-management program in Europe, and the subject of a variety of long-term monitoring programs. We examined two formulations of an IPM, but ultimately relied on the one that provided a satisfactory fit to all the available data as based on Chi-squared goodness of fit tests. Our analyses suggest a negative bias in November counts (-20 %), a negative bias in capture-mark-recapture estimates of survival (-3 %), and a negative bias in indices of productivity (-23 %). We offer possible explanations for these biases, whether the degree of bias seems reasonable considering those explanations, and how bias might be investigated directly and ultimately avoided or corrected. Finally, we discuss implications of our work for developing IPMs and associated monitoring programs for managing pink-footed geese and other waterbird species.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2019.108869","usgsCitation":"Johnson, F., Zimmerman, G.S., Jensen, G.H., Clausen, K.K., Frederiksen, M., and Madsen, J., 2020, Using integrated population models for insights into monitoring programs: An application using pink-footed geese: Ecological Modelling, v. 415, 108869, 13 p., https://doi.org/10.1016/j.ecolmodel.2019.108869.","productDescription":"108869, 13 p.","ipdsId":"IP-107877","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":437202,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P901K3RP","text":"USGS data release","linkHelpText":"Demographic parameters for Svalbard pink-footed geese, 1991-2018"},{"id":369802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"415","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Fred 0000-0002-5854-3695","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":220964,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":776392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerman, Guthrie S.","contributorId":42473,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie","email":"","middleInitial":"S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":776393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jensen, Gitte H.","contributorId":220965,"corporation":false,"usgs":false,"family":"Jensen","given":"Gitte","email":"","middleInitial":"H.","affiliations":[{"id":13685,"text":"Aarhus University, Department of Bioscience","active":true,"usgs":false}],"preferred":false,"id":776394,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clausen, Kevin K.","contributorId":174355,"corporation":false,"usgs":false,"family":"Clausen","given":"Kevin","email":"","middleInitial":"K.","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":776395,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frederiksen, Morten","contributorId":217509,"corporation":false,"usgs":false,"family":"Frederiksen","given":"Morten","email":"","affiliations":[{"id":13685,"text":"Aarhus University, Department of Bioscience","active":true,"usgs":false}],"preferred":false,"id":776396,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Madsen, Jesper","contributorId":178168,"corporation":false,"usgs":false,"family":"Madsen","given":"Jesper","email":"","affiliations":[],"preferred":false,"id":776397,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70236239,"text":"70236239 - 2020 - Directivity of M 3.1 earthquake near Anza, California and the effect on peak ground motion","interactions":[],"lastModifiedDate":"2022-08-31T14:19:50.242428","indexId":"70236239","displayToPublicDate":"2019-11-19T09:14:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Directivity of M 3.1 earthquake near Anza, California and the effect on peak ground motion","docAbstract":"We show the effect of rupture directivity on peak ground‐motion values for a moderate magnitude event at Anza, California, and neighboring stations at the Imperial Valley. The event was located near Borrego Springs on the west side of the Salton Sea and was well recorded at broadband stations near Anza, California, and at stations on the west side of the Imperial Valley. After correcting for regional attenuation, an anomalously large residual in peak motion was observed at station ERR just to the southeast of the epicenter. Using the algorithm from Boatwright (2007), peak motions from the regional seismic networks in southern California were inverted to determine directivity, which was to the southeast along the trend of the San Jacinto fault toward station ERR. This algorithm uses peak values compiled for the ShakeMap system mostly at regional distances. It does not capture the main features of the source time function (STF) predicted by directivity. Consequently, we determined the second‐degree moments for this earthquake, which confirmed that station ERR has a shorter and higher STF compared to stations to the northwest suggesting rupture propagated to the southeast. The azimuthal distribution of local stations is sparse, but nevertheless the largest amplitudes (such as at station ERR) correlate well with the maximum in the radiation pattern and smaller values with the minima, which is the radiation pattern for SH plus the effect of directivity. Using the data from the analysis of the second‐degree moments, the characteristic length of the fault is 0.58 km, assuming an idealized unilateral extended rupture with a rupture time of 0.09 s. This yields an apparent rupture velocity of
We develop a novel method of estimating population size from imperfectly detected counts of individuals and a separate estimate of detection probability. Observed counts are separated into classes within which detection probability is assumed constant. Within a detection class, counts are modeled as a single binomial observation X with success probability p where the goal is to estimate index N. We use a Horvitz–Thompson‐like estimator for N and account for uncertainty in both sample data and estimated success probability via a parametric bootstrap. Unlike capture–recapture methods, our model does not require repeated sampling of the population. Our method is able to achieve good results, even with small X. We show in a factorial simulation study that the median of the bootstrapped sample has small bias relative to N and that coverage probabilities of confidence intervals for N are near nominal under a wide array of scenarios. Our methodology begins to break down when P(X=0)>0.1 but is still capable of obtaining reasonable confidence coverage. We illustrate the proposed technique by estimating (1) the size of a moose population in Alaska and (2) the number of bat fatalities at a wind power facility, both from samples with imperfect detection probabilities, estimated independently.
Coral reefs are among the most species-rich, productive and economically valuable ecosystems on Earth but increasingly frequent pantropical coral bleaching events are threatening their persistence on a global scale. The 2015–2016 El Niño led to the hottest sea surface temperatures on record and widespread bleaching of shallow-water corals. However, the causes of spatial variation in bleaching are poorly understood, and near-surface estimates of heat stress, such as those inferred from satellites, cannot be generalized across the broad depth ranges occupied by corals. Here, using in situ temperatures recorded across reefs from the near surface to 30–50 m depths in the western, central and eastern Pacific, we show that during the peak of the 2015–2016 anomaly, temperature fluctuations associated with internal waves reduced cumulative heat exposure by up to 88%. The durations of severe thermal anomalies above 8 °C-days, at which point widespread coral bleaching and mortality are likely, were also decreased by >36% at some sites and were prevented entirely at others. The impact of internal waves across depths on coral reefs has the potential to create and support thermal refuges in which heat stress and coral bleaching risk may be modulated, but future effects depend on the response of internal wave climates to continued warming and strengthening ocean stratification.
","language":"English","publisher":"Nature","doi":"10.1038/s41561-019-0486-4","usgsCitation":"Wyatt, A.S., Leichter, J., Toth, L., Miyajima, T., Aronson, R.B., and Nagata, T., 2020, Heat accumulation on coral reefs mitigated by internal waves: Nature Geoscience, v. 13, p. 28-34, https://doi.org/10.1038/s41561-019-0486-4.","productDescription":"7 p.","startPage":"28","endPage":"34","ipdsId":"IP-106803","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":422976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2019-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Wyatt, Alex S. J. 0000-0002-1339-9546","orcid":"https://orcid.org/0000-0002-1339-9546","contributorId":331743,"corporation":false,"usgs":false,"family":"Wyatt","given":"Alex","email":"","middleInitial":"S. J.","affiliations":[{"id":79277,"text":"University of Tokyo, Japan","active":true,"usgs":false}],"preferred":false,"id":888673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leichter, James J.","contributorId":261128,"corporation":false,"usgs":false,"family":"Leichter","given":"James J.","affiliations":[{"id":52738,"text":"SCRIPPS INSTITUTION OF OCEANOGRAPHY, UNIVERSITY OF CALIFORNIA AT SAN DIEGO","active":true,"usgs":false}],"preferred":false,"id":888674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":888675,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miyajima, Toshihiro 0000-0001-8562-6704","orcid":"https://orcid.org/0000-0001-8562-6704","contributorId":331744,"corporation":false,"usgs":false,"family":"Miyajima","given":"Toshihiro","email":"","affiliations":[{"id":79277,"text":"University of Tokyo, Japan","active":true,"usgs":false}],"preferred":false,"id":888676,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aronson, Richard B. 0000-0003-0383-3844","orcid":"https://orcid.org/0000-0003-0383-3844","contributorId":212695,"corporation":false,"usgs":false,"family":"Aronson","given":"Richard","email":"","middleInitial":"B.","affiliations":[{"id":17748,"text":"Florida Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":888677,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagata, Toshi","contributorId":331745,"corporation":false,"usgs":false,"family":"Nagata","given":"Toshi","email":"","affiliations":[{"id":79277,"text":"University of Tokyo, Japan","active":true,"usgs":false}],"preferred":false,"id":888678,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227189,"text":"70227189 - 2020 - Life history structure of westslope cutthroat trout: Inferences from otolith microchemistry","interactions":[],"lastModifiedDate":"2022-01-04T15:28:45.816391","indexId":"70227189","displayToPublicDate":"2019-11-18T09:23:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Life history structure of westslope cutthroat trout: Inferences from otolith microchemistry","docAbstract":"Life history diversity is important for population stability and is dependent on connectivity to habitat that supports all life stages and life history strategies for a species. Westslope Cutthroat Trout Oncorhynchus clarkii lewisi (WCT) exhibit plasticity in life history strategies in response to environmental variability, but fisheries managers have been challenged with evaluating the life history structure of WCT populations. The goals of this research were to use strontium isotopes (i.e., 87Sr/86Sr) derived from ambient water and sagittal otoliths to assess spatial variability and describe the life history structure of WCT. Water samples (n = 49) and WCT (n = 571) sagittal otoliths were collected throughout the Coeur d’Alene Lake basin in Idaho and analyzed for Sr isotopes. Model-based discriminant function analysis was used to assign WCT to natal tributaries and to infer maternal origins. Life history structure was inferred from maternal signatures and indicated that fluvial (68% of all fish), resident (27%), and adfluvial (5%) life history strategies were present. Connectivity in lotic systems and from lotic to lentic environments supports WCT life history diversity and contributes to a broad distribution of the species.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2019.105416","usgsCitation":"Heckel, J.W., Quist, M.C., Watkins, C.J., and Dux, A.M., 2020, Life history structure of westslope cutthroat trout: Inferences from otolith microchemistry: Fisheries Research, v. 222, 105416, 14 p., https://doi.org/10.1016/j.fishres.2019.105416.","productDescription":"105416, 14 p.","ipdsId":"IP-107684","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":393855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Coeur d'Alene Lake, Coeur d'Alene River, St, Joe River, St, Maries River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 46.75\n ],\n [\n -115,\n 46.75\n ],\n [\n -115,\n 48\n ],\n [\n -117,\n 48\n ],\n [\n -117,\n 46.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"222","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Heckel, John W","contributorId":270716,"corporation":false,"usgs":false,"family":"Heckel","given":"John","email":"","middleInitial":"W","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":830023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":830022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watkins, Carson J.","contributorId":171708,"corporation":false,"usgs":false,"family":"Watkins","given":"Carson","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":830024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dux, Andrew M.","contributorId":175256,"corporation":false,"usgs":false,"family":"Dux","given":"Andrew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":830025,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70219557,"text":"70219557 - 2020 - Post-fire aspen (Populus tremuloides) regeneration varies in response to winter precipitation across a regional climate gradient","interactions":[],"lastModifiedDate":"2021-04-13T12:48:22.205733","indexId":"70219557","displayToPublicDate":"2019-11-18T07:45:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Post-fire aspen (Populus tremuloides) regeneration varies in response to winter precipitation across a regional climate gradient","docAbstract":"Altered climate and changing fire regimes are synergistically impacting forest communities globally, resulting in deviations from historical norms and creation of novel successional dynamics. These changes are particularly important when considering the stability of a keystone species such as quaking aspen (Populus tremuloides Michx.), which contributes critical ecosystem services across its broad North American range. As a relatively drought intolerant species, projected changes of altered precipitation timing, amount, and type (e.g. snow or rain) may influence aspen response to fire, especially in moisture-limited and winter precipitation-dominated portions of its range. Aspen is generally considered an early-seral species that benefits from fire, but increases in fire activity across much of the western United States could affect the species in unpredictable ways. This study examined post-fire aspen stands across a regional climate gradient spanning from the north-central Great Basin to the northeastern portion of the Greater Yellowstone Ecosystem (USA). We investigated the influence of seasonal precipitation and temperature variables, snowpack, and site conditions (e.g. browsing levels, topography) on density of post-fire aspen regeneration (i.e. all small trees ha−1) and recruitment (i.e. small trees ≥2 m tall ha−1) across 15 fires that occurred between 2000 and 2009. The range of post-fire regeneration (2500–71,600 small trees ha−1) and recruitment (0–32,500 small trees ≥2 m ha−1) densities varied widely across plots. Linear mixed effects models demonstrated that both response variables increased primarily with early winter (Oct-Dec) precipitation during the ‘fire-regen period’ (i.e., fire year and five years after fire) relative to the 30-year mean. The 30-year mean of early winter precipitation and fire-regen period snowpack were also positively related to recruitment densities. Both response variables decreased with higher shrub cover, highlighting the importance of considering shrub competition in post-fire environments. Regeneration and recruitment densities were negatively related to proportion browsed aspen leaders and animal pellet densities (no./m2), respectively, indicating the influence of ungulate browsing even at the relatively low levels observed across sites. A post-hoc exploratory analysis suggests that deviation in early winter precipitation during the fire-regen period (relative to 30-year means) varied among sites along directional gradients, emphasizing the need to consider multiple spatiotemporal scales when investigating climate effects on post-fire successional dynamics. We discuss our findings in terms of dynamic management and conservation strategies in light of changing fire regimes and climate conditions.
Many studies have examined the effects of climate warming on lake stability, but few have addressed environmental changes concomitant with climate change, such as alterations in water clarity and lake inflow. Although air temperature rise is a predominant factor linked to lake thermal characteristics, climate-driven changes at watershed scales can substantially alter lake clarity and inflow, exacerbating the effects of future air warming on lake thermal conditions. Without accounting for potential changes in clarity and inflow, future thermal predictions could be inaccurate. We employed the General Lake Model to simulate future thermal conditions (relative thermal resistance to mixing; RTRM) of small (< 12 ha) mountain lakes of the western United States by calibrating the model to a set of lakes in the Southern Rocky Mountains, USA. We found that after air temperature, alterations in inflow had the largest effect on lake thermal conditions, changes in wind had the least effect, and larger lakes experienced more than double the increase in lake stability than smaller lakes. Generally, clear, high inflow lakes had the lowest stability now, and in the future, while the largest overall increase in thermal stability occurred in larger lakes with low inflows and high turbidity. Assuming air temperature rise alone, summer stability of mountain lakes of the western United States was predicted to increase by 15–23% at + 2 °C air temperatures, and by 39–62% at + 5 °C air temperatures. When accounting for associated changes in clarity and inflow, lake stability was predicted to increase by 208% with + 2 °C air warming and 318% with at 5 °C air warming. Thus, ignoring the multivariate effects of climate change can substantially underestimate changes to mountain lake thermal and stratification regimes. Dimictic lakes may become more strongly stratified and polymictic lakes will experience more prolonged stratification. While predicted changes to lake temperatures may not be harmful to trout species that currently inhabit mountain lakes, longer and more intense stratification could cause indirect effects, such as hypoxia, that could reduce growth and survival of these organisms.
","language":"English","publisher":"Springer","doi":"10.1007/s00027-019-0676-6","usgsCitation":"Christianson, K.R., Johnson, B.M., and Hooten, M., 2020, Compound effects of water clarity, inflow, wind and climate warming on mountain lake thermal regimes: Aquatic Sciences, v. 82, 6, 17 p., https://doi.org/10.1007/s00027-019-0676-6.","productDescription":"6, 17 p.","ipdsId":"IP-107101","costCenters":[{"id":189,"text":"Colorado Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":393652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rawah Wilderness Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.89035034179688,\n 40.534676780615406\n ],\n [\n -105.85052490234375,\n 40.58058466412761\n ],\n [\n -105.83816528320312,\n 40.693134153308065\n ],\n [\n -105.88897705078125,\n 40.80029619806279\n ],\n [\n -105.96313476562499,\n 40.88029480552824\n ],\n [\n -106.09771728515625,\n 40.86991083161536\n ],\n [\n -106.11968994140624,\n 40.84498264925404\n ],\n [\n -106.0125732421875,\n 40.727486422997785\n ],\n [\n -105.96450805664062,\n 40.61916465186328\n ],\n [\n -105.89035034179688,\n 40.534676780615406\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2019-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Christianson, Kyle R.","contributorId":270655,"corporation":false,"usgs":false,"family":"Christianson","given":"Kyle","email":"","middleInitial":"R.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":829700,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Brett M.","contributorId":270656,"corporation":false,"usgs":false,"family":"Johnson","given":"Brett","email":"","middleInitial":"M.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":829701,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":829699,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70209054,"text":"70209054 - 2020 - A temporally stratified extension of space‐for‐time Cormack–Jolly–Seber for migratory animals","interactions":[],"lastModifiedDate":"2020-09-10T19:45:16.648168","indexId":"70209054","displayToPublicDate":"2019-11-15T12:55:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1039,"text":"Biometrics","active":true,"publicationSubtype":{"id":10}},"title":"A temporally stratified extension of space‐for‐time Cormack–Jolly–Seber for migratory animals","docAbstract":"Understanding drivers of temporal variation in demographic parameters is a central goal of mark‐recapture analysis. To estimate the survival of migrating animal populations in migration corridors, space‐for‐time mark–recapture models employ discrete sampling locations in space to monitor marked populations as they move past monitoring sites, rather than the standard practice of using fixed sampling points in time. Because these models focus on estimating survival over discrete spatial segments, model parameters are implicitly integrated over the temporal dimension. Furthermore, modeling the effect of time‐varying covariates on model parameters is complicated by unknown passage times for individuals that are not detected at monitoring sites. To overcome these limitations, we extended the Cormack–Jolly–Seber (CJS) framework to estimate temporally stratified survival and capture probabilities by including a discretized arrival time process in a Bayesian framework. We allow for flexibility in the model form by including temporally stratified covariates and hierarchical structures. In addition, we provide tools for assessing model fit and comparing among alternative structural models for the parameters. We demonstrate our framework by fitting three competing models to estimate daily survival, capture, and arrival probabilities at four hydroelectric dams for over 200 000 individually tagged migratory juvenile salmon released into the Snake River, USA.","language":"English","publisher":"Wiley","doi":"10.1111/biom.13171","usgsCitation":"Hance, D.J., Perry, R., Plumb, J., and Pope, A., 2020, A temporally stratified extension of space‐for‐time Cormack–Jolly–Seber for migratory animals: Biometrics, v. 76, no. 3, p. 900-912, https://doi.org/10.1111/biom.13171.","productDescription":"13 p.","startPage":"900","endPage":"912","ipdsId":"IP-106158","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":373199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Hance, Dalton J. 0000-0002-4475-706X dhance@usgs.gov","orcid":"https://orcid.org/0000-0002-4475-706X","contributorId":206496,"corporation":false,"usgs":true,"family":"Hance","given":"Dalton","email":"dhance@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784643,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":223235,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784644,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plumb, John 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":223236,"corporation":false,"usgs":true,"family":"Plumb","given":"John","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784645,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pope, Adam C. 0000-0002-7253-2247","orcid":"https://orcid.org/0000-0002-7253-2247","contributorId":223237,"corporation":false,"usgs":true,"family":"Pope","given":"Adam","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784646,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211826,"text":"70211826 - 2020 - The mineral diversity of Jezero crater: Evidence for possible lacustrine carbonates on Mars","interactions":[],"lastModifiedDate":"2020-08-07T22:03:59.417806","indexId":"70211826","displayToPublicDate":"2019-11-11T17:00:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"The mineral diversity of Jezero crater: Evidence for possible lacustrine carbonates on Mars","docAbstract":"Noachian-aged Jezero crater is the only known location on Mars where clear orbital detections of carbonates are found in close proximity to clear fluvio-lacustrine features indicating the past presence of a paleolake; however, it is unclear whether or not the carbonates in Jezero are related to the lacustrine activity. This distinction is critical for evaluating the astrobiological potential of the site, as lacustrine carbonates on Earth are capable of preserving biosignatures at scales that may be detectable by a landed mission like the Mars 2020 rover, which is planned to land in Jezero in February 2021. In this study, we conduct a detailed investigation of the mineralogical and morphological properties of geological units within Jezero crater in order to better constrain the origin of carbonates in the basin and their timing relative to fluvio-lacustrine activity. Using orbital visible/near-infrared hyperspectral images from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) along with high resolution imagery and digital elevation models, we identify a distinct carbonate-bearing unit, the “Marginal Carbonates,” located along the inner margin of the crater, near the largest inlet valley and the western delta. Based on their strong carbonate signatures, topographic properties, and location in the crater, we propose that this unit may preserve authigenic lacustrine carbonates, precipitated in the near-shore environment of the Jezero paleolake. Comparison to carbonate deposits from terrestrial closed basin lakes suggests that if the Marginal Carbonates are lacustrine in origin, they could preserve macro- and microscopic biosignatures in microbialite rocks like stromatolites, some of which would likely be detectable by Mars 2020. The Marginal Carbonates may represent just one phase of a complex fluvio-lacustrine history in Jezero crater, as we find that the spectral diversity of the fluvio-lacustrine deposits in the crater is consistent with a long-lived lake system cataloging the deposition and erosion of regional geologic units. Thus, Jezero crater may contain a unique record of the evolution of surface environments, climates, and habitability on early Mars.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2019.113526","usgsCitation":"Horgan, B., Anderson, R.B., Dromart, G., Amador, E.S., and Rice, M.S., 2020, The mineral diversity of Jezero crater: Evidence for possible lacustrine carbonates on Mars: Icarus, v. 339, 113526, 34 p., https://doi.org/10.1016/j.icarus.2019.113526.","productDescription":"113526, 34 p.","ipdsId":"IP-111142","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":458525,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.icarus.2019.113526","text":"Publisher Index Page"},{"id":377214,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"339","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Horgan, Briony H. N.","contributorId":237069,"corporation":false,"usgs":false,"family":"Horgan","given":"Briony H. N.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":795256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Ryan B. 0000-0003-4465-2871 rbanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-4465-2871","contributorId":170054,"corporation":false,"usgs":true,"family":"Anderson","given":"Ryan","email":"rbanderson@usgs.gov","middleInitial":"B.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":795257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dromart, G.","contributorId":237771,"corporation":false,"usgs":false,"family":"Dromart","given":"G.","affiliations":[{"id":47605,"text":"U. Lyon","active":true,"usgs":false}],"preferred":false,"id":795258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Amador, Elena S.","contributorId":237804,"corporation":false,"usgs":false,"family":"Amador","given":"Elena","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":795345,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rice, Melissa S.","contributorId":237772,"corporation":false,"usgs":false,"family":"Rice","given":"Melissa","email":"","middleInitial":"S.","affiliations":[{"id":47606,"text":"Western Washington U.","active":true,"usgs":false}],"preferred":false,"id":795259,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208112,"text":"70208112 - 2020 - Seasonal variation in sediment delivery across the bay-marsh interface of an estuarine salt marsh","interactions":[],"lastModifiedDate":"2020-01-27T19:20:35","indexId":"70208112","displayToPublicDate":"2019-11-08T19:19:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal variation in sediment delivery across the bay-marsh interface of an estuarine salt marsh","docAbstract":"Sediment transport across bay–marsh interfaces depends on wave energy, vegetation, and marsh-edge morphology, and varies over a range of timescales. We investigated these dynamics in a tidal salt marsh with a gently-sloped, vegetated edge adjacent to northern San Francisco Bay. Spartina foliosa (cordgrass) inhabits the lower marsh and Salicornia pacifica (pickleweed) predominates on the marsh plain. We measured suspended-sediment concentration (SSC) and hydrodynamics in bay shallows and along a 100-m cross-shore transect in the marsh, during winter and summer. Four-year averaged accretion measured with marker-horizon plots was twice as great along the marsh transect as adjacent to a tidal creek, 50 m from the bay. We estimated deposition and trapping efficiency from the time-series data to assess its variation with season and wave energy. At high tide the transition zone (between cordgrass and pickleweed) was usually erosional, the pickleweed zone was depositional, and both erosion and deposition increased with wave energy, as did the landward position of maximum deposition. Erosion from the transition zone accounted for approximately one-third of the sediment flux into the pickleweed. In the pickleweed zone, SSC, the difference between flood- and ebb-tide SSC and trapping efficiency were greater in summer than winter for comparable wave conditions, which we attribute to increased sediment trapping by dense summer cordgrass. Moderate waves in summer (46%) accounted for more annual accretion in the pickleweed zone than larger waves in winter (28%), although the contribution of winter storms was diminished by the dry winter during the study.","language":"English","publisher":"Wiley","doi":"10.1029/2019JC015268","usgsCitation":"Lacy, J.R., Foster-Martinez, M.R., Allen, R., Ferner, M.C., and Callaway, J.C., 2020, Seasonal variation in sediment delivery across the bay-marsh interface of an estuarine salt marsh: Journal of Geophysical Research C: Oceans, v. 125, no. 1, e2019JC015268, https://doi.org/10.1029/2019JC015268.","productDescription":"e2019JC015268","ipdsId":"IP-108231","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":371615,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.04687499999999,\n 37.21283151445594\n ],\n [\n -121.6845703125,\n 37.21283151445594\n ],\n [\n -121.6845703125,\n 38.30718056188316\n ],\n [\n -123.04687499999999,\n 38.30718056188316\n ],\n [\n -123.04687499999999,\n 37.21283151445594\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":780520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster-Martinez, Madeline R.","contributorId":201705,"corporation":false,"usgs":false,"family":"Foster-Martinez","given":"Madeline","email":"","middleInitial":"R.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":780521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Rachel 0000-0002-0284-6466","orcid":"https://orcid.org/0000-0002-0284-6466","contributorId":221857,"corporation":false,"usgs":true,"family":"Allen","given":"Rachel","email":"","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":780522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ferner, Matthew C.","contributorId":176972,"corporation":false,"usgs":false,"family":"Ferner","given":"Matthew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":780523,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Callaway, John C. 0000-0002-7364-286X","orcid":"https://orcid.org/0000-0002-7364-286X","contributorId":205456,"corporation":false,"usgs":false,"family":"Callaway","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":37110,"text":"Dept. of Environmental Science, University of San Francisco, 2130 Fulton St., San Francisco, CA 94117","active":true,"usgs":false}],"preferred":false,"id":780524,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70212701,"text":"70212701 - 2020 - #EarthquakeAdvisory: Exploring discourse between government officials, news media and social media during the Bombay Beach 2016 Swarm","interactions":[],"lastModifiedDate":"2020-08-27T15:25:27.575316","indexId":"70212701","displayToPublicDate":"2019-11-06T06:55:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"#EarthquakeAdvisory: Exploring discourse between government officials, news media and social media during the Bombay Beach 2016 Swarm","docAbstract":"Communicating probabilities of natural hazards to varied audiences is a notoriously difficult task. Many of these challenges were encountered during the 2016 Bombay Beach, California, swarm of ~100 2≤M≤4.3 earthquakes, which began on 26 September 2016 and lasted for several days. The swarm’s proximity to the southern end of the San Andreas fault caused concern that a larger earthquake could be triggered. Within 1–2 days, different forecast models were used to evaluate the likelihood of a larger event with two agencies (the U.S. Geological Survey [USGS] and the California Governor’s Office of Emergency Services) releasing probabilities and forecasts for larger earthquakes. Our research explores communication and news media efforts, as well as how people on a microblogging social media site (Twitter) responded to these forecasts. Our findings suggest that news media used a combination of information sources, basing their articles on what they learned from social media, as well as using information provided by government agencies. As the swarm slowed down, there is evidence of the continued interplay between news media and social media, with the USGS issuing revised probability reports and scientists from the USGS and other institutions participating in media interviews. In reporting on the swarm, news media often used language more generally than the scientists; terms such as probability, likelihood, chance, and possibility were used interchangeably. Knowledge of how news media used scientific information from the 2016 Bombay Beach forecasts can assist local, state, and federal agencies in developing effective communication strategies to respond to future earthquakes.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190082","usgsCitation":"McBride, S., Llenos, A.L., Page, M.T., and van der Elst, N., 2020, #EarthquakeAdvisory: Exploring discourse between government officials, news media and social media during the Bombay Beach 2016 Swarm: Seismological Research Letters, v. 91, no. 1, p. 438-451, https://doi.org/10.1785/0220190082.","productDescription":"14 p.","startPage":"438","endPage":"451","ipdsId":"IP-104404","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":377873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Imperial County","otherGeospatial":"Bombay Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.740966796875,\n 33.330528249028085\n ],\n [\n -115.63247680664062,\n 33.330528249028085\n ],\n [\n -115.63247680664062,\n 33.37641235124676\n ],\n [\n -115.740966796875,\n 33.37641235124676\n ],\n [\n -115.740966796875,\n 33.330528249028085\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"91","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"McBride, Sara K. 0000-0002-8062-6542","orcid":"https://orcid.org/0000-0002-8062-6542","contributorId":206933,"corporation":false,"usgs":true,"family":"McBride","given":"Sara K.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":797308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Llenos, Andrea L. 0000-0002-4088-6737 allenos@usgs.gov","orcid":"https://orcid.org/0000-0002-4088-6737","contributorId":4455,"corporation":false,"usgs":true,"family":"Llenos","given":"Andrea","email":"allenos@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":797309,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":797310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van der Elst, Nicholas 0000-0002-3812-1153 nvanderelst@usgs.gov","orcid":"https://orcid.org/0000-0002-3812-1153","contributorId":147858,"corporation":false,"usgs":true,"family":"van der Elst","given":"Nicholas","email":"nvanderelst@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":797311,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70212820,"text":"70212820 - 2020 - Grazing-induced changes to biological soil crust cover mediate hillslope erosion in a long-term exclosure experiment","interactions":[],"lastModifiedDate":"2020-08-31T13:19:26.065099","indexId":"70212820","displayToPublicDate":"2019-11-05T08:17:15","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6002,"text":"Rangeland Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"Grazing-induced changes to biological soil crust cover mediate hillslope erosion in a long-term exclosure experiment","docAbstract":"Dryland ecosystems are particularly vulnerable to erosion generated by livestock grazing. Quantifying this risk across a variety of landscape settings is essential for successful adaptive management, particularly in light of a changing climate. In the Upper Colorado River Basin, there are nearly 25 000 km2 of rangelands with underlying soils derived from Mancos Shale, an erodible and saline geologic parent material. Salinity is a major concern within the Colorado River watershed, much of which is attributed to runoff and leaching from Mancos Shale deposits. In a 60-yr paired-watershed experiment in western Colorado, we used silt fences to measure differences in saline hillslope erosion, including both total sediment yield and concentrations of primary saline constituents (Na and Se), in watersheds that were either exposed to grazing or where livestock was excluded. After accounting for the strong effects of soil type, slope, and antecedent precipitation, we found that grazing increased sediment loss by ≈50% across our 8-yr time series (0.1–1.5 tn ha−1), consistent with levels reported at the watershed scale in early published work from studies at the same location. Eroded sediment Se levels were low and unaffected by grazing history, but Na concentrations were significantly reduced on grazed hillslopes, likely due to depletion of surface Na in soils exposed to chronic soil disturbance by livestock. Variable selection and path analysis identified that biological soil crust (BSC) cover, more than any other variable, explained the differences in sediment yields between grazed and ungrazed watersheds, partially through the enhancement of soil aggregate stability. Our results suggest that BSC cover should be granted heightened consideration in rangeland decision support tools (e.g., state-and-transition models) and that measures to reduce surface disturbance from livestock such as altering the timing or intensity of grazing may be effective for reducing downstream impacts.
Individuals should prefer and use habitats that confer high fitness, but habitat use is not always adaptive. Vegetation in natural landscapes changes gradually and the ability of species to adaptively adjust their habitat use to long-term changes is largely unstudied. We studied nest patch and territory use over 28 yr in Orange-crowned Warblers (Oreothlypis celata) in a system that has undergone natural long-term changes in vegetation. Abundance of maple (Acer grandidentatum), its preferred nesting habitat, gradually declined from 1987 to 2015. We examined whether habitat use and its fitness consequences changed as the availability of preferred habitat decreased. We used resource selection function models to determine changes over time in the probability of using a nest patch given available patches, and the probability of using a territory given available territories. We estimated nest survival to evaluate changes over time in the fitness consequences of nest patch use. We also compared habitat use (nest patch and territory) and fitness (nest survival) between areas with naturally reduced abundance of maple and experimentally increased abundance of maple (fenced areas). Nest patch use depended on maple abundance and did not change drastically across 28 yr, even though the availability of preferred maple patches decreased over time. In contrast, nest survival tended to decrease over time. We did not see differences in nest patch use and nest survival between unfenced and fenced areas, unlike territory use, which increased with the abundance of maple in fenced areas and decreased in unfenced areas. Our study depicts one example of relatively unchanged habitat use in the face of decreased availability of preferred vegetation across years, with a resulting decrease in reproductive success. Investigating changes in habitat use and fitness consequences for animals exposed to long-term habitat change is necessary to understand adaptive behavioral responses.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.1093/auk/ukz061","usgsCitation":"Fierro-Calderón, K., and Martin, T.E., 2020, Does vegetation change over 28 years affect habitat use and reproductive success?: The Auk, v. 137, no. 1, p. 1-9, https://doi.org/10.1093/auk/ukz061.","productDescription":"ukz061, 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-107208","costCenters":[{"id":399,"text":"Montana Cooperative Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":458549,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/auk/ukz061","text":"Publisher Index Page"},{"id":393648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Mogollon Rim","volume":"137","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Fierro-Calderón, Karolina","contributorId":270677,"corporation":false,"usgs":false,"family":"Fierro-Calderón","given":"Karolina","affiliations":[{"id":48645,"text":"umt","active":true,"usgs":false}],"preferred":false,"id":829732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Thomas E. 0000-0002-4028-4867 tmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-4028-4867","contributorId":1208,"corporation":false,"usgs":true,"family":"Martin","given":"Thomas","email":"tmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":829731,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227771,"text":"70227771 - 2020 - Nonlinear reaction–diffusion process models improve inference for population dynamics","interactions":[],"lastModifiedDate":"2022-01-31T15:47:25.634954","indexId":"70227771","displayToPublicDate":"2019-11-03T09:40:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1577,"text":"Environmetrics","active":true,"publicationSubtype":{"id":10}},"title":"Nonlinear reaction–diffusion process models improve inference for population dynamics","docAbstract":"Partial differential equations (PDEs) are a useful tool for modeling spatiotemporal dynamics of ecological processes. However, as an ecological process evolves, we need statistical models that can adapt to changing dynamics as new data are collected. We developed a model that combines an ecological diffusion equation and logistic growth to characterize colonization processes of a population that establishes long-term equilibrium over a heterogeneous environment. We also developed a homogenization strategy to statistically upscale the PDE for faster computation and adopted a hierarchical framework to accommodate multiple data sources collected at different spatial scales. We highlighted the advantages of using a logistic reaction component instead of a Malthusian component when population growth demonstrates asymptotic behavior. As a case study, we demonstrated that our model improves spatiotemporal abundance forecasts of sea otters in Glacier Bay, Alaska. Furthermore, we predicted spatially varying local equilibrium abundances as a result of environmentally driven diffusion and density-regulated growth. Integrating equilibrium abundances over the study area in our application enabled us to infer the overall carrying capacity of sea otters in Glacier Bay, Alaska.
","language":"English","publisher":"Wiley","doi":"10.1002/env.2604","usgsCitation":"Lu, X., Williams, P.J., Hooten, M., Powell, J.A., Womble, J., and Bower, M.R., 2020, Nonlinear reaction–diffusion process models improve inference for population dynamics: Environmetrics, v. 31, no. 3, e2604, 17 p., https://doi.org/10.1002/env.2604.","productDescription":"e2604, 17 p.","ipdsId":"IP-109015","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":458552,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/env.2604","text":"Publisher Index Page"},{"id":395142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Glacier Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -137.18902587890625,\n 58.32247223302053\n ],\n [\n -135.64819335937497,\n 58.32247223302053\n ],\n [\n -135.64819335937497,\n 59.1\n ],\n [\n -137.18902587890625,\n 59.1\n ],\n [\n -137.18902587890625,\n 58.32247223302053\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Lu, Xinyi","contributorId":272582,"corporation":false,"usgs":false,"family":"Lu","given":"Xinyi","email":"","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":832169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Perry J.","contributorId":169058,"corporation":false,"usgs":false,"family":"Williams","given":"Perry","email":"","middleInitial":"J.","affiliations":[{"id":25400,"text":"U.S. Fish and Wildlife Service, Big Oaks National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":832170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":832171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powell, James A.","contributorId":190683,"corporation":false,"usgs":false,"family":"Powell","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":12682,"text":"Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":832172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Womble, Jamie N.","contributorId":267709,"corporation":false,"usgs":false,"family":"Womble","given":"Jamie N.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":832173,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bower, Michael R.","contributorId":198632,"corporation":false,"usgs":false,"family":"Bower","given":"Michael","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":832174,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70209553,"text":"70209553 - 2020 - Change points in annual peak streamflows: Method comparisons and historical change points in the United States","interactions":[],"lastModifiedDate":"2020-05-04T17:54:54.253292","indexId":"70209553","displayToPublicDate":"2019-11-02T07:59:37","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Change points in annual peak streamflows: Method comparisons and historical change points in the United States","docAbstract":"Change-point, or step-trend, detection is an active area of research in statistics and an area of great interest in hydrology because change points may be evidence of natural or anthropogenic changes in climatic, hydrologic, or landscape processes. A common change-point technique is the Pettitt test; however, many change-point methods are now available and testing of methods has been limited. This study investigated eight methods for detecting change points in the location (central tendency, seven methods) and scale (dispersion or spread, one method) of annual peak streamflows, using simulated data with and without change points, and peak-streamflow series from basins with known large additions of reservoir storage. Parametric methods tested, including a Bayesian one, did not perform well, even when transforming peak streamflows to approximate normality by using logarithms. Nonparametric methods other than the Pettitt test allow for more than one change point but have an unacceptable number of false positives. Based on the results of our methods comparisons, we used the Pettitt and the Mood tests to find change points in location and scale, respectively, in thousands of streamgage records in the conterminous United States. Change points in location (median) and scale are abundant, with the changes in median peak streamflow showing regional patterns, as well as a strong increased streamflow signal around 1970. The changes in scale of peak streamflows are dominated more by temporal than spatial patterns; more streamgages had decreases in scale in earlier decades than recent decades and more streamgages had increases in scale occurring in recent decades than earlier decades.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2019.124307","collaboration":"","usgsCitation":"Ryberg, K.R., Hodgkins, G.A., and Dudley, R., 2020, Change points in annual peak streamflows: Method comparisons and historical change points in the United States: Journal of Hydrology, v. 583, https://doi.org/10.1016/j.jhydrol.2019.124307.","productDescription":"124307, 13 p.","startPage":"","ipdsId":"IP-098428","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":373948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": 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,{"id":70208374,"text":"70208374 - 2020 - Hydrologic modeling for flow-ecology science in the Southeastern United States and Puerto Rico","interactions":[],"lastModifiedDate":"2020-02-05T17:51:21","indexId":"70208374","displayToPublicDate":"2019-11-01T17:50:59","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":32,"text":"General Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"SRS-246","title":"Hydrologic modeling for flow-ecology science in the Southeastern United States and Puerto Rico","docAbstract":"An understanding of the applicability and utility of hydrologic models is critical to support the effective management of water resources throughout the Southeastern United States (SEUS) and Puerto Rico (PR). Hydrologic models have the capacity to provide an estimate of the quantity of available water at ungauged locations (i.e., areas of the country where a U.S. Geological Survey [USGS] continuous record gauge is not installed) and provide the baseline flow information necessary to develop the linkages between water availability and characteristics of streamflow that support ecological communities (i.e., support the development of flow-ecology response models). This report inventories and then directly examines and compares a subset of hydrologic models used to estimate streamflow at a number of gauged basins across the SEUS and PR. This effort was designed to evaluate, quantify, and compare the magnitude of error and to investigate the potential causes of error associated with predicted streamflows from seven hydrologic models of varying complexity and calibration strategy. This was accomplished by computing and then comparing classical hydrologic model fit statistics (e.g., mean bias, coefficient of determination [R2], root mean squared error [RMSE], Nash-Sutcliffe Efficiency [NSE]) and understanding the bias in the prediction in these and a subset of ecologically relevant flow metrics (ERFMs). Additionally, streamflow predictions from a larger regional-scale hydrologic model were compared to those of several fine-scale hydrologic models under a range of hypothetical climate change scenarios to determine the range of predicted streamflow responses to fixed climate perturbations. A pilot study was conducted using predicted streamflow and boosted regression trees to develop a set of predictive flow-ecology response models to assess the potential change in fish species richness in the North Carolina Piedmont under several scenarios of water availability change. This report is intended to provide a general assessment of all the tools and techniques available to support hydrologic modeling for flow-ecology science in the SEUS and PR. It is our hope that the approach used herein to understand differences in streamflow predictions among a subset of hydrologic models that have been applied in the SEUS for developing flow-ecology response models will provide water resource managers and stakeholders with an informed pathway for developing the capacity to link streamflow and ecological response and an understanding of some of the limitations associated with these type of modeling efforts.
","language":"English","publisher":"U.S. Department of Agriculture Forest Service","usgsCitation":"Caldwell, P.V., Kennen, J., Hain, E.F., Nelson, S.A., Sun, G., and McNulty, S., 2020, Hydrologic modeling for flow-ecology science in the Southeastern United States and Puerto Rico: General Technical Report SRS-246, iii, 77 p.","productDescription":"iii, 77 p.","ipdsId":"IP-098574","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":372111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372091,"type":{"id":15,"text":"Index Page"},"url":"https://www.srs.fs.usda.gov/pubs/59109"}],"country":"United States","state":"Alabama, Florida, Georgia, Mississippi, North Carolina, Puerto Rico, South Carolina, Tennessee, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.06640625,\n 30.44867367928756\n ],\n [\n -85.25390625,\n 29.611670115197377\n ],\n [\n -84.287109375,\n 29.99300228455108\n ],\n [\n -82.880859375,\n 28.998531814051795\n ],\n [\n -81.298828125,\n 30.675715404167743\n ],\n [\n -78.31054687499999,\n 33.50475906922609\n ],\n [\n -75.849609375,\n 34.66935854524543\n ],\n [\n -75.673828125,\n 36.10237644873644\n ],\n [\n -76.552734375,\n 36.527294814546245\n ],\n [\n -80.068359375,\n 36.66841891894786\n ],\n [\n -80.771484375,\n 37.3002752813443\n ],\n [\n -82.08984375,\n 37.3002752813443\n ],\n [\n -83.84765625,\n 36.4566360115962\n ],\n [\n -87.5390625,\n 35.60371874069731\n ],\n [\n -89.736328125,\n 34.813803317113155\n ],\n [\n -89.56054687499999,\n 30.44867367928756\n ],\n [\n -88.06640625,\n 30.44867367928756\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.2747802734375,\n 17.868975338932746\n ],\n [\n -65.23681640625,\n 17.868975338932746\n ],\n [\n -65.23681640625,\n 18.531700307384043\n ],\n [\n -67.2747802734375,\n 18.531700307384043\n ],\n [\n -67.2747802734375,\n 17.868975338932746\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Caldwell, Peter V.","contributorId":222249,"corporation":false,"usgs":false,"family":"Caldwell","given":"Peter","email":"","middleInitial":"V.","affiliations":[{"id":39172,"text":"USDA Forest Service, Center for Forest Watershed Science, Coweeta Hydrologic Laboratory, Otto, NC, USA","active":true,"usgs":false}],"preferred":false,"id":781654,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781653,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hain, Ernie F.","contributorId":141247,"corporation":false,"usgs":false,"family":"Hain","given":"Ernie","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":781655,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Stacy A.C.","contributorId":222250,"corporation":false,"usgs":false,"family":"Nelson","given":"Stacy","email":"","middleInitial":"A.C.","affiliations":[{"id":39171,"text":"Center for Geospatial Analytics, Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, 27695, USA","active":true,"usgs":false}],"preferred":false,"id":781656,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sun, Ge","contributorId":145893,"corporation":false,"usgs":false,"family":"Sun","given":"Ge","email":"","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":781657,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McNulty, Steven G.","contributorId":222251,"corporation":false,"usgs":false,"family":"McNulty","given":"Steven G.","affiliations":[{"id":39173,"text":"USDA Forest Service, Eastern Forest Environmental Threat Assessment Center, Raleigh, NC, USA","active":true,"usgs":false}],"preferred":false,"id":781658,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}