There is an urgent need for near-term predictions of ecological restoration outcomes despite imperfect knowledge of ecosystems. Restoration outcomes are always uncertain but integrating Bayesian modeling into the process of adaptive management allows researchers and practitioners to explicitly incorporate prior knowledge of ecosystems into future predictions. Although barriers exist, employing qualitative expert knowledge and previous case studies can help narrow the range of uncertainty in forecasts. Software and processes that allow for repeatable methodologies can help bridge the existing gap between theory and application of Bayesian methods in adaptive management.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.13596","usgsCitation":"Applestein, C., Caughlin, T.T., and Germino, M., 2022, Bayesian modeling can facilitate adaptive management in restoration: Restoration Ecology, v. 30, no. 4, e13596, 4 p., https://doi.org/10.1111/rec.13596.","productDescription":"e13596, 4 p.","ipdsId":"IP-132611","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":401973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Applestein, Cara 0000-0002-7923-8526","orcid":"https://orcid.org/0000-0002-7923-8526","contributorId":218010,"corporation":false,"usgs":true,"family":"Applestein","given":"Cara","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caughlin, T. Trevor","contributorId":218133,"corporation":false,"usgs":false,"family":"Caughlin","given":"T.","email":"","middleInitial":"Trevor","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":844467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844440,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70254666,"text":"70254666 - 2022 - Recursive Bayesian computation facilitates adaptive optimal design in ecological studies","interactions":[],"lastModifiedDate":"2024-06-06T12:15:39.819355","indexId":"70254666","displayToPublicDate":"2021-10-28T07:13:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Recursive Bayesian computation facilitates adaptive optimal design in ecological studies","docAbstract":"Optimal design procedures provide a framework to leverage the learning generated by ecological models to flexibly and efficiently deploy future monitoring efforts. At the same time, Bayesian hierarchical models have become widespread in ecology and offer a rich set of tools for ecological learning and inference. However, coupling these methods with an optimal design framework can become computationally intractable. Recursive Bayesian computation offers a way to substantially reduce this computational burden, making optimal design accessible for modern Bayesian ecological models. We demonstrate the application of so-called prior-proposal recursive Bayes to optimal design using a simulated data binary regression and the real-world example of monitoring and modeling sea otters in Glacier Bay, Alaska. These examples highlight the computational gains offered by recursive Bayesian methods and the tighter fusion of monitoring and science that those computational gains enable.
Trees in the urban right-of-way areas have increasingly been considered part of a suite of green infrastructure practices used to manage stormwater runoff. A paired-catchment experimental design (with street tree removal as the treatment) was used to assess how street trees affect major hydrologic fluxes in a typical residential stormwater collection and conveyance network. The treatment consisted of removing 29 green ash (Fraxinus pennsylvanica) and two Norway maple (Acer platanoides) street trees from a medium-density residential area. Tree removal resulted in an estimated 198 m3 increase in surface runoff volume compared to the control catchment over the course of the study. This increase accounted for 4% of the total measured runoff after trees were removed. Despite significant changes to runoff volume (p ≤ 0.10), peak discharge was generally not affected by tree removal. On a per-tree basis, 66 L of rainfall per m2 of canopy was lost that would have otherwise been intercepted and stored. Runoff volume reduction benefit was estimated at 6376 L per tree. These values experimentally document per-capita retention services rendered by trees over a growing season with 42 storm events. These values are within the range reported by previous studies, which largely relied on simulation. This study provides catchment scale evidence that reducing stormwater runoff is one of many ecosystem services provided by street trees. This study quantifies these services, based on site conditions and a mix of deciduous species, and serves to improve our ability to account for this important yet otherwise poorly constrained hydrologic service. Engineers, city planners, urban foresters, and others involved with the management of urban stormwater can use this information to better understand tradeoffs involved in using green infrastructure to reduce urban runoff burden.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.151296","usgsCitation":"Selbig, W.R., Loheid, S., Schuster, W., Scharenbroch, B.C., Coville, R.C., Kruegler, J., Avery, W., Haefner, R.J., and Nowak, D., 2022, Quantifying the stormwater runoff volume reduction benefits of urban street tree canopy: Science of the Total Environment, v. 806, no. 3, 151296, 9 p., https://doi.org/10.1016/j.scitotenv.2021.151296.","productDescription":"151296, 9 p.","ipdsId":"IP-131647","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":436043,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JJHBVW","text":"USGS data release","linkHelpText":"Storm event data in the control and test catchments during the calibration and treatment phase of a urban tree canopy study in Fond du Lac, Wisconsin, from May 2018 through September 2020: U.S. Geological Survey data release"},{"id":392624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Fond du Lac","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.516845703125,\n 43.70163689691259\n ],\n [\n -88.34930419921875,\n 43.70163689691259\n ],\n [\n -88.34930419921875,\n 43.85235516793534\n ],\n [\n -88.516845703125,\n 43.85235516793534\n ],\n [\n -88.516845703125,\n 43.70163689691259\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"806","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loheid, Steven P. II 0000-0003-1897-0163","orcid":"https://orcid.org/0000-0003-1897-0163","contributorId":269846,"corporation":false,"usgs":false,"family":"Loheid","given":"Steven P.","suffix":"II","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":828022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schuster, William","contributorId":117899,"corporation":false,"usgs":true,"family":"Schuster","given":"William","email":"","affiliations":[],"preferred":false,"id":828040,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scharenbroch, Bryant C. 0000-0002-9342-7550","orcid":"https://orcid.org/0000-0002-9342-7550","contributorId":269849,"corporation":false,"usgs":false,"family":"Scharenbroch","given":"Bryant","email":"","middleInitial":"C.","affiliations":[{"id":17613,"text":"University of Wisconsin - Stevens Point","active":true,"usgs":false}],"preferred":false,"id":828041,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coville, Robert C. 0000-0002-6895-2564","orcid":"https://orcid.org/0000-0002-6895-2564","contributorId":269851,"corporation":false,"usgs":false,"family":"Coville","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":40823,"text":"Davey Institute","active":true,"usgs":false}],"preferred":false,"id":828042,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kruegler, James 0000-0002-2671-0807","orcid":"https://orcid.org/0000-0002-2671-0807","contributorId":269853,"corporation":false,"usgs":false,"family":"Kruegler","given":"James","email":"","affiliations":[{"id":40823,"text":"Davey Institute","active":true,"usgs":false}],"preferred":false,"id":828043,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Avery, William 0000-0002-2651-9906","orcid":"https://orcid.org/0000-0002-2651-9906","contributorId":269858,"corporation":false,"usgs":false,"family":"Avery","given":"William","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":828044,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Haefner, Ralph J. 0000-0002-4363-9010 rhaefner@usgs.gov","orcid":"https://orcid.org/0000-0002-4363-9010","contributorId":1793,"corporation":false,"usgs":true,"family":"Haefner","given":"Ralph","email":"rhaefner@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828045,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nowak, David 0000-0002-2043-0062","orcid":"https://orcid.org/0000-0002-2043-0062","contributorId":269856,"corporation":false,"usgs":false,"family":"Nowak","given":"David","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":828046,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70229767,"text":"70229767 - 2022 - Accuracy of histology, endoscopy, ultrasonography, and plasma sex steroids in describing the population reproductive structure of hatchery-origin and wild white sturgeon","interactions":[],"lastModifiedDate":"2022-03-17T16:21:20.800086","indexId":"70229767","displayToPublicDate":"2021-10-27T11:16:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2166,"text":"Journal of Applied Ichthyology","active":true,"publicationSubtype":{"id":10}},"title":"Accuracy of histology, endoscopy, ultrasonography, and plasma sex steroids in describing the population reproductive structure of hatchery-origin and wild white sturgeon","docAbstract":"Hatchery-origin white sturgeon Acipenser transmontanus in the lower Columbia River, Canada are approaching puberty, and describing the reproductive structure of the population is critical to determine if they are capable of contributing to spawning events in the wild, a key management uncertainty. Few studies have compared the accuracy of available tools (histology, ultrasound, endoscopy, and plasma sex steroids) used to assign sex and stage of maturity within the same population of prepubertal and post-pubertal sturgeon. Population reproductive structure was described using these tools in 332 hatchery-origin and 75 wild individuals over 2 years (2017 and 2018). True sex was determined using histological analysis of gonadal tissue, which is 100% accurate at assigning sex and stage of maturity in fish when germ cells are present in the biopsy. All hatchery-origin fish assessed had not reached puberty and were pre-meiotic males (n = 158) or pre-vitellogenic females (n = 174). Assignment of true sex using histology was 97% in hatchery-origin and 94% in wild fish as several biopsies did not contain germ cells. Fish with gonadal biopsies that did not contain germ cells and intersex fish (n = 3) were not included in further analyses of other tools. Accuracy in assigning sex to both the hatchery-origin (98%) and wild (100%) fish was highest using endoscopy (an otoscope). The other tools evaluated were less accurate, with 69% accuracy in hatchery-origin and 74% accuracy in wild fish for plasma sex steroids and 57% accuracy in hatchery-origin and 70% accuracy in wild fish for ultrasonography. Based on these results, endoscopy was the most reliable tool for assigning sex in both prepubertal and post-pubertal fish and can be easily complimented with histology when determining stage of maturity or describing population reproductive structure.
","language":"English","publisher":"Wiley","doi":"10.1111/jai.14280","usgsCitation":"Maskill, P.A., Crossman, J.A., Webb, M., Marrello, M.M., and Guy, C.S., 2022, Accuracy of histology, endoscopy, ultrasonography, and plasma sex steroids in describing the population reproductive structure of hatchery-origin and wild white sturgeon: Journal of Applied Ichthyology, v. 38, no. 1, p. 3-16, https://doi.org/10.1111/jai.14280.","productDescription":"14 p.","startPage":"3","endPage":"16","ipdsId":"IP-127673","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449583,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jai.14280","text":"Publisher Index Page"},{"id":397257,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, Washington","otherGeospatial":"Columbia River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.10577392578124,\n 48.67826727167941\n ],\n [\n -117.49053955078125,\n 48.67826727167941\n ],\n [\n -117.49053955078125,\n 49.3948875168789\n ],\n [\n -118.10577392578124,\n 49.3948875168789\n ],\n [\n -118.10577392578124,\n 48.67826727167941\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-10-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Maskill, Paige A. C.","contributorId":288695,"corporation":false,"usgs":false,"family":"Maskill","given":"Paige","email":"","middleInitial":"A. C.","affiliations":[{"id":61831,"text":"Montana Cooperative Fishery Research Unit, Department of Ecology","active":true,"usgs":false}],"preferred":false,"id":838230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crossman, James A.","contributorId":288696,"corporation":false,"usgs":false,"family":"Crossman","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":37568,"text":"BC Hydro","active":true,"usgs":false}],"preferred":false,"id":838231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Molly A. H.","contributorId":288697,"corporation":false,"usgs":false,"family":"Webb","given":"Molly A. H.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":838232,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marrello, Marco M.","contributorId":288698,"corporation":false,"usgs":false,"family":"Marrello","given":"Marco","email":"","middleInitial":"M.","affiliations":[{"id":61834,"text":"Terraquatic Resource Management","active":true,"usgs":false}],"preferred":false,"id":838233,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":838229,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254822,"text":"70254822 - 2022 - Tracking the desert's edge with a Pleistocene relict","interactions":[],"lastModifiedDate":"2024-06-10T15:11:12.973342","indexId":"70254822","displayToPublicDate":"2021-10-27T10:05:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Tracking the desert's edge with a Pleistocene relict","docAbstract":"In addition to the Sky Islands of the southwestern U.S. and northwestern Mexico, a series of 900–1200 m desert peaks surrounded by arid lowlands support temperate affiliated species at their summits. The presence of disjunct long-lived plant taxa on under-explored desert mountains, especially Isla Tiburón at 29° latitude in the Gulf of California, suggests a more southerly extent of Ice Age woodlands than previously understood. The phylogeography of the desert edge species Canotia holacantha (Celastraceae) was investigated to test the hypothesis that insular desert peak populations represent remnants of Pleistocene woodlands rather than recent dispersal events. Sequences of four chloroplast DNA regions totaling 2032 bp were amplified from 74 individuals of 14 populations across the entire range of C. holacantha as well as nine individuals that represented the other two species in its clade (C. wendtii and Acanthothamnus aphyllus) and two outgroups. Results suggest that a Canotia common ancestor occurred on the landscape, which underwent a population contraction ca. 15 kya. The Isla Tiburón C. holacantha population and the Chihuahuan Desert microendemic C. wendtii have the greatest genetic differentiation, are sister to one another, and basal to all other Canotia populations. Three haplotypes within C. holacantha were recovered, which correspond to regional geography and thus identified as the Arizona, Sonora, and Tiburón haplotypes, within which Acanthothamnus aphyllus is nested rather than as a sister genus. These results indicate a once broad distribution of Canotia/Acanthothamnus when the current peripheral desert ecotone habitat was more widespread during the Pleistocene, now present in relict populations on the fringes of the southern desert, in the Chihuahuan Desert, with scattered populations on desert peaks, and a common or abundant distribution at the northern boundary of the Sonoran Desert. These results suggest Canotia has tracked the shift of the desert's edge both in latitude and elevation since the end of the last Ice Age.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2021.104653","usgsCitation":"Wilder, B., Becker, A.T., Munguia-Vega, A., and Culver, M., 2022, Tracking the desert's edge with a Pleistocene relict: Journal of Arid Environments, v. 196, 104653, 9 p., https://doi.org/10.1016/j.jaridenv.2021.104653.","productDescription":"104653, 9 p.","ipdsId":"IP-132306","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":429756,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.03889363159188,\n 34.44633288560905\n ],\n [\n -118.03889363159188,\n 23.186795096665634\n ],\n [\n -104.79132977024277,\n 23.186795096665634\n ],\n [\n -104.79132977024277,\n 34.44633288560905\n ],\n [\n -118.03889363159188,\n 34.44633288560905\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"196","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wilder, Benjamin T.","contributorId":337736,"corporation":false,"usgs":false,"family":"Wilder","given":"Benjamin T.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":902645,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Becker, Amanda T.","contributorId":337737,"corporation":false,"usgs":false,"family":"Becker","given":"Amanda","email":"","middleInitial":"T.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":902646,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munguia-Vega, Adrian","contributorId":337738,"corporation":false,"usgs":false,"family":"Munguia-Vega","given":"Adrian","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":902647,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Culver, Melanie 0000-0001-5380-3059 mculver@usgs.gov","orcid":"https://orcid.org/0000-0001-5380-3059","contributorId":197693,"corporation":false,"usgs":true,"family":"Culver","given":"Melanie","email":"mculver@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902644,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70225644,"text":"70225644 - 2022 - Tectonic influence on axial-transverse sediment routing in the Denver Basin","interactions":[],"lastModifiedDate":"2021-10-29T14:02:45.567435","indexId":"70225644","displayToPublicDate":"2021-10-27T08:57:37","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Tectonic influence on axial-transverse sediment routing in the Denver Basin","docAbstract":"Detrital zircon U-Pb and (U-Th)/He ages from latest Cretaceous–Eocene strata of the Denver Basin provide novel insights into evolving sediment sourcing, recycling, and dispersal patterns during deposition in an intracontinental foreland basin. In total, 2464 U-Pb and 78 (U-Th)/He analyses of detrital zircons from 21 sandstone samples are presented from outcrop and drill core in the proximal and distal portions of the Denver Basin. Upper Cretaceous samples that predate uplift of the southern Front Range during the Laramide orogeny (Pierre Shale, Fox Hills Sandstone, and Laramie Formation) contain prominent Late Cretaceous (84–77 Ma), Jurassic (169–163 Ma), and Proterozoic (1.69–1.68 Ga) U-Pb ages, along with less abundant Paleozoic through Archean zircon grain ages. These grain ages are consistent with sources in the western U.S. Cordillera, including the Mesozoic Cordilleran magmatic arc and Yavapai-Mazatzal basement, with lesser contributions of Grenville and Appalachian zircon recycled from older sedimentary sequences. Mesozoic zircon (U-Th)/He ages confirm Cordilleran sources and/or recycling from the Sevier orogenic hinterland. Five of the 11 samples from syn-Laramide basin fill (latest Cretaceous–Paleocene D1 Sequence) and all five samples from the overlying Eocene D2 Sequence are dominated by 1.1–1.05 Ga zircon ages that are interpreted to reflect local derivation from the ca. 1.1 Ga Pikes Peak batholith. Corresponding late Mesoproterozoic to early Neoproterozoic zircon (U-Th)/He ages are consistent with local sourcing from the southern Front Range that underwent limited Mesozoic–Cenozoic unroofing. The other six samples from the D1 Sequence yielded detrital zircon U-Pb ages similar to pre-Laramide units, with major U-Pb age peaks at ca. 1.7 and 1.4 Ga but lacking the 1.1 Ga age peak found in the other syn-Laramide samples. One of these samples yielded abundant Mesozoic and Paleozoic (U-Th)/He ages, including prominent Early and Late Cretaceous peaks.
We propose that fill of the Denver Basin represents the interplay between locally derived sediment delivered by transverse drainages that emanated from the southern Front Range and a previously unrecognized, possibly extraregional, axial-fluvial system. Transverse alluvial-fluvial fans, preserved in proximal basin fill, record progressive unroofing of southern Front Range basement during D1 and D2 Sequence deposition. Deposits of the upper and lower D1 Sequence across the basin were derived from these fans that emanated from the southern Front Range. However, the finer-grained, middle portion of the D1 Sequence that spans the Cretaceous-Paleogene boundary was deposited by both transverse (proximal basin fill) and axial (distal basin fill) fluvial systems that exhibit contrasting provenance signatures. Although both tectonic and climatic controls likely influenced the stratigraphic development of the Denver Basin, the migration of locally derived fans toward and then away from the thrust front suggests that uplift of the southern Front Range may have peaked at approximately the Cretaceous-Paleogene boundary.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Tectonic evolution of the Sevier-Laramide hinterland, thrust belt, and foreland, and postorogenic slab rollback (180–20 Ma)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2021.2555(11)","usgsCitation":"Sharman, G.R., Stockli, D.F., Flaig, P., Raynolds, R., Dechesne, M., and Covault, J.A., 2022, Tectonic influence on axial-transverse sediment routing in the Denver Basin, chap. of Tectonic evolution of the Sevier-Laramide hinterland, thrust belt, and foreland, and postorogenic slab rollback (180–20 Ma), 20 p., https://doi.org/10.1130/2021.2555(11).","productDescription":"20 p.","ipdsId":"IP-117384","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":449586,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1130/spe.s.16850272","text":"External Repository"},{"id":391158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Denver Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.435546875,\n 38.151837403006766\n ],\n [\n -103.60107421874999,\n 38.151837403006766\n ],\n [\n -103.60107421874999,\n 41.178653972331674\n ],\n [\n -106.435546875,\n 41.178653972331674\n ],\n [\n -106.435546875,\n 38.151837403006766\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sharman, Glenn R","contributorId":268171,"corporation":false,"usgs":false,"family":"Sharman","given":"Glenn","email":"","middleInitial":"R","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":826041,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stockli, Daniel F. 0000-0001-7652-2129","orcid":"https://orcid.org/0000-0001-7652-2129","contributorId":254375,"corporation":false,"usgs":false,"family":"Stockli","given":"Daniel","email":"","middleInitial":"F.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":826042,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flaig, Peter","contributorId":268172,"corporation":false,"usgs":false,"family":"Flaig","given":"Peter","email":"","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":826043,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Raynolds, Robert","contributorId":268173,"corporation":false,"usgs":false,"family":"Raynolds","given":"Robert","affiliations":[{"id":27833,"text":"Denver Museum of Nature and Science","active":true,"usgs":false}],"preferred":false,"id":826044,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dechesne, Marieke 0000-0002-4468-7495","orcid":"https://orcid.org/0000-0002-4468-7495","contributorId":213936,"corporation":false,"usgs":true,"family":"Dechesne","given":"Marieke","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":826045,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Covault, Jacob A","contributorId":265637,"corporation":false,"usgs":false,"family":"Covault","given":"Jacob","email":"","middleInitial":"A","affiliations":[{"id":54745,"text":"Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX","active":true,"usgs":false}],"preferred":false,"id":826046,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70226527,"text":"70226527 - 2022 - The role of preexisting upper plate strike-slip faults during long-lived (ca. 30 Myr) oblique flat slab subduction, southern Alaska","interactions":[],"lastModifiedDate":"2021-11-23T14:16:17.67564","indexId":"70226527","displayToPublicDate":"2021-10-27T08:13:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"The role of preexisting upper plate strike-slip faults during long-lived (ca. 30 Myr) oblique flat slab subduction, southern Alaska","docAbstract":"Upper plates of subduction zones commonly respond to flat slab subduction by structural reactivation, magmatic arc disruption, and foreland basin inversion. However, the role of active strike-slip faults in focusing convergent deformation and magmatism in response to oblique flat slab subduction remains less clear. Here, we present new detrital apatite fission-track (dAFT) ages from 12 modern catchments in the eastern Alaska Range, Alaska, USA, to reveal how the dextral Denali fault system has facilitated bedrock exhumation and topographic growth during ca. 30 Ma-to-present oblique flat slab subduction of the Yakutat oceanic plateau. Additionally, a 940 ka (40Ar/39Ar whole rock) basalt flow is spatially associated with Cenozoic structures, locally reset AFT ages and provides the first evidence for Quaternary volcanism along the southern flank of the eastern Alaska Range. We integrate our new data with other thermochronologic, geochronologic, and regional geologic datasets to show that (1) most high topography regions in southern Alaska have undergone rapid bedrock cooling and exhumation since ca. 30 Ma; (2) elevated terrain and young cooling are spatially associated with long-lived active strike-slip fault systems; (3) topographic growth associated with strike-slip fault deformation led to local inversion of basin systems and drainage reorganization; (4) the onset of oblique oceanic plateau subduction is coeval with a southward shift in arc magmatism from one region of active strike-slip faulting to another above the northeastern edge of the flat slab; and (5) Quaternary volcanism marks the revival of magmatism in the eastern Alaska Range above the geophysically imaged northeastern edge of the flat slab. Our analysis of the post-30 Ma geologic evolution of southern Alaska demonstrates that strike-slip fault systems that were active at the time of slab flattening evolved into transpression zones that focused bedrock cooling, rock exhumation, and topographic growth.
Sediment eroded from the headwaters of a large basin strongly influences channels and ecosystems far downstream, but the connection is often difficult to trace. Disturbance-dependent riparian trees are thought to rely primarily on floods for formation of the sand bars necessary for seedling establishment, but pulses of sediment should also promote formation of such features. In order to expand understanding of the role of sediment connectivity in governing ecological processes, here we explore the hypothesis that cottonwood forest along the Green and Yampa Rivers in Utah and Colorado are dominated by trees established a century ago during a period of extensive channel migration caused by significant headwater erosion. Analysis of historical documents and aerial photographs suggests that three key tributaries of the Yampa River underwent significant historical erosion from roughly 1880 to 1940. Average width and depth of tributaries with defined arroyos increased two to six times from historical surveys, resulting in the export of ~30 million metric tons of sediment, sizably increasing the sediment load and channel migration rate of the Yampa and Green Rivers. Establishment of major portions of several downstream cottonwood forests occurred during this period of historical erosion, increased sediment loads, and heightened channel migration rates, and the area of forest dating to that time is much greater than can be explained by high flows alone. Viewed collectively, our findings suggest tributary erosion played a vital role in successful downstream forest establishment, a link we contend is best illustrated through a sediment-ecological connectivity framework. Broadly, this framework facilitates consideration of linkages between morphological and ecological processes at the watershed-scale. Development and utilization of a watershed-scale sediment-ecological connectivity perspective highlights the value of sediment as a critical ecological resource to be managed jointly with flow to ensure the maintenance of vital riverine ecosystems.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.5277","usgsCitation":"Kemper, J.T., Thaxton, R.D., Rathburn, S.L., Friedman, J.M., Mueller, E., and Scott, M.L., 2022, Sediment-ecological connectivity in a large river network: Earth Surface Processes and Landforms, v. 47, no. 2, p. 639-657, https://doi.org/10.1002/esp.5277.","productDescription":"19 p.","startPage":"639","endPage":"657","ipdsId":"IP-127871","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":392853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah","otherGeospatial":"Green River, Yampa River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.11572265625,\n 38.013476231041935\n ],\n [\n -105.633544921875,\n 38.013476231041935\n ],\n [\n -105.633544921875,\n 40.93841495689795\n ],\n [\n -111.11572265625,\n 40.93841495689795\n ],\n [\n -111.11572265625,\n 38.013476231041935\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Kemper, John T.","contributorId":270040,"corporation":false,"usgs":false,"family":"Kemper","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":828338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thaxton, R. D.","contributorId":270041,"corporation":false,"usgs":false,"family":"Thaxton","given":"R.","email":"","middleInitial":"D.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":828339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rathburn, Sara L.","contributorId":140606,"corporation":false,"usgs":false,"family":"Rathburn","given":"Sara","email":"","middleInitial":"L.","affiliations":[{"id":13539,"text":"Department of Geosciences, Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":828340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Friedman, Jonathan M. 0000-0002-1329-0663","orcid":"https://orcid.org/0000-0002-1329-0663","contributorId":44495,"corporation":false,"usgs":true,"family":"Friedman","given":"Jonathan","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":828341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mueller, Erich R. 0000-0001-8202-154X","orcid":"https://orcid.org/0000-0001-8202-154X","contributorId":207750,"corporation":false,"usgs":false,"family":"Mueller","given":"Erich R.","affiliations":[{"id":37626,"text":"Department of Geography, University of Wyoming, Laramie, WY, USA","active":true,"usgs":false}],"preferred":false,"id":828342,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scott, Michael L.","contributorId":204827,"corporation":false,"usgs":false,"family":"Scott","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":828343,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70231451,"text":"70231451 - 2022 - Next-generation lampricides: A three-stage process to develop improved control tools for invasive sea lamprey","interactions":[],"lastModifiedDate":"2022-05-11T11:37:08.337092","indexId":"70231451","displayToPublicDate":"2021-10-26T06:34:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Next-generation lampricides: A three-stage process to develop improved control tools for invasive sea lamprey","docAbstract":"The advent of Low Power Wide Area Networks (LPWAN) has improved the feasibility of wireless sensor networks for environmental sensing across wide areas. We have built EnviSense, an ultra-low power environmental sensing system, and deployed over a dozen of them across two locations in Northern California for hydrological monitoring applications with the U.S. Geological Survey (USGS). This paper details our experiences with the design and implementation of this system across two years, including six months of continuous measurement in the field. We describe the lessons learned for deployment planning, remote device management and programming, and system co-design with a domain-expert from the USGS.
","largerWorkTitle":"LP-IoT '21: Proceedings of the 1st ACM Workshop on No Power and Low Power Internet-of-Things","language":"English","publisher":"Association of Computing Machinery","doi":"10.1145/3477085.3478988","usgsCitation":"Grimsley, R., Marineau, M.D., and Iannucci, R.A., 2022, Experiences in LP-IoT: EnviSense deployment of remotely reprogrammable environmental sensors, in LP-IoT '21: Proceedings of the 1st ACM Workshop on No Power and Low Power Internet-of-Things, p. 1-7, https://doi.org/10.1145/3477085.3478988.","productDescription":"7 p.","startPage":"1","endPage":"7","ipdsId":"IP-130093","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":449595,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1145/3477085.3478988","text":"Publisher Index Page"},{"id":396759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Beale Air Force Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.42982482910158,\n 39.066380823434486\n ],\n [\n -121.36528015136717,\n 39.06718050308463\n ],\n [\n -121.31996154785158,\n 39.087169549791966\n ],\n [\n -121.31927490234376,\n 39.13325601865834\n ],\n [\n -121.34056091308594,\n 39.14949897356036\n ],\n [\n -121.3985824584961,\n 39.176650950983294\n ],\n [\n -121.47239685058592,\n 39.16227768020765\n ],\n [\n -121.48097991943358,\n 39.14630393428414\n ],\n [\n -121.4813232421875,\n 39.12633165289992\n ],\n [\n -121.42982482910158,\n 39.066380823434486\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2021-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Grimsley, Reese 0000-0002-3458-0707","orcid":"https://orcid.org/0000-0002-3458-0707","contributorId":287982,"corporation":false,"usgs":false,"family":"Grimsley","given":"Reese","email":"","affiliations":[{"id":12943,"text":"Carnegie Mellon University","active":true,"usgs":false}],"preferred":false,"id":837249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marineau, Mathieu D. 0000-0002-6568-0743 mmarineau@usgs.gov","orcid":"https://orcid.org/0000-0002-6568-0743","contributorId":4954,"corporation":false,"usgs":true,"family":"Marineau","given":"Mathieu","email":"mmarineau@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iannucci, Robert A.","contributorId":202339,"corporation":false,"usgs":false,"family":"Iannucci","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":36393,"text":"Carnegie Mellon University - Silicon Valley","active":true,"usgs":false}],"preferred":false,"id":837251,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70230213,"text":"70230213 - 2022 - Temperature-based modeling of incubation period to protect loggerhead hatchlings on an urban beach in Northwest Florida","interactions":[],"lastModifiedDate":"2022-04-05T15:19:54.312558","indexId":"70230213","displayToPublicDate":"2021-10-25T10:16:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2277,"text":"Journal of Experimental Marine Biology and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Temperature-based modeling of incubation period to protect loggerhead hatchlings on an urban beach in Northwest Florida","docAbstract":"Sea turtle hatchlings face many natural and anthropogenic threats during their short journey to the water after emerging from nests. Reducing hatchling mortality is critical to population recovery of imperiled sea turtle species; however, protecting hatchlings is particularly challenging on beaches degraded by human development and disturbances, including artificial lighting. Managers need practical methods to reduce hatchling mortality without harming their natural behavior or development. To address this need, we describe an approach to reduce mortality of loggerhead hatchlings that relies on prediction of clutch incubation length and knowledge of hatchling emergence patterns. We developed models to predict incubation length utilizing sand temperature and nest depth data from 133 loggerhead nests laid on an urban beach in Northwest Florida from 2013 to 2020. Incubation length was predicted to within 2.2 days using mean sand temperatures measured just outside of the clutch. Predicted accuracy improved to 1.9 days using a 2-parameter model incorporating sand temperature and measured depth to the topmost eggs. Hatchlings emerged almost exclusively at night in a single large group with no evidence of asynchronous emergences. Emergence times were skewed toward the early evening, in contrast to loggerhead nests on the Florida Atlantic coast which tend to hatch near midnight. Using these prediction tools, monitoring efforts could be focused on days and times of expected emergence to enable protection of hatchlings emerging naturally from nests left in situ. The method used here, while not a substitute for recovery of degraded nesting habitat, provides a way to protect hatchlings that avoids disturbing the eggs with instruments or restraining the hatchlings with cages or screens.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jembe.2021.151647","usgsCitation":"Watson, K.P., and Lamont, M., 2022, Temperature-based modeling of incubation period to protect loggerhead hatchlings on an urban beach in Northwest Florida: Journal of Experimental Marine Biology and Ecology, v. 546, 151647, 10 p., https://doi.org/10.1016/j.jembe.2021.151647.","productDescription":"151647, 10 p.","ipdsId":"IP-127739","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":398117,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","county":"Bay County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.528564453125,\n 30.023921574501376\n ],\n [\n -85.8856201171875,\n 30.235340577517942\n ],\n [\n -85.92819213867188,\n 30.22466172703242\n ],\n [\n -85.59860229492188,\n 30.0286775329042\n ],\n [\n -85.54504394531249,\n 30.00013836058068\n ],\n [\n -85.528564453125,\n 30.023921574501376\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"546","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Watson, Kennard P.","contributorId":289668,"corporation":false,"usgs":false,"family":"Watson","given":"Kennard","email":"","middleInitial":"P.","affiliations":[{"id":62225,"text":"Panama City Beach Turtle Watch","active":true,"usgs":false}],"preferred":false,"id":839570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":222403,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":839571,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70225602,"text":"70225602 - 2022 - Ontogeny of eDNA shedding during early development in Chinook Salmon (Oncorhynchus tshawytscha)","interactions":[],"lastModifiedDate":"2022-04-11T16:36:52.660548","indexId":"70225602","displayToPublicDate":"2021-10-24T07:20:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5840,"text":"Environmental DNA","active":true,"publicationSubtype":{"id":10}},"title":"Ontogeny of eDNA shedding during early development in Chinook Salmon (Oncorhynchus tshawytscha)","docAbstract":"Knowledge of the timing of major life history events in aquatic species is important for informing conservation and resource management planning. Accordingly, surveys of environmental DNA (eDNA) have been performed to determine the efficacy of eDNA for providing information on life history events, primarily focusing on the timing of events associated with spawning, and these studies have proved successful. However, spawning represents only one part of the life history, and therefore, information on eDNA shedding during other life history stages is needed to fill gaps in knowledge. Here, we explored eDNA shedding during early life history (from fertilized eggs until near yolk sac absorption) in Chinook Salmon (Oncorhynchus tshawytscha) at three biomasses in a laboratory environment. We found that fertilized eggs shed little eDNA prior to hatching. Hatching coincided with a spike in eDNA, and we observed a significant and positive relationship between eDNA concentration and the number of hatched eggs. The concentration of eDNA shed by larvae after hatching was not consistent across post-hatch sampling days, suggesting developmental and behavioral changes associated with larval ontogeny may affect eDNA shedding rate. These results indicate that eDNA data may be used to identify hatch timing and verify successful reproduction in oviparous aquatic fishes. The application of eDNA to early life history broadens the capacity of eDNA-based methods for assessing population status and trends.
Accurate information on diet composition is central to understanding and conserving carnivore populations. Quantitative fatty acid signature analysis (QFASA) has emerged as a powerful tool for estimating the diets of predators, but ambiguities remain about the timeframe of QFASA estimates and the need to account for species-specific patterns of metabolism. We conducted a series of feeding experiments with four juvenile male brown bears (Ursus arctos) to (1) track the timing of changes in adipose tissue composition and QFASA diet estimates in response to a change in diet and (2) quantify the relationship between consumer and diet FA composition (i.e., determine “calibration coefficients”). Bears were fed three compositionally distinct diets for 90–120 days each. Two marine-based diets were intended to approximate the lipid content and composition of the wild diet of polar bears (U. maritimus). Bear adipose tissue composition changed quickly in the direction of the diet and showed evidence of stabilization after 60 days. During hibernation, FA profiles were initially stable but diet estimates after 10 weeks were sensitive to calibration coefficients. Calibration coefficients derived from the marine-based diets were broadly similar to each other and to published values from marine-fed mink (Mustela vison), which have been used as a model for free-ranging polar bears. For growing bears on a high-fat diet, the temporal window for QFASA estimates was 30–90 days. Although our results reinforce the importance of accurate calibration, the similarities across taxa and diets suggest it may be feasible to develop a generalized QFASA approach for mammalian carnivores.
Some northern Wisconsin lakes have shown declines in catches of age-0 Walleye Sander vitreus in standardized fall electrofishing sampling, suggesting that recruitment bottlenecks are occurring in the first several months of life. In 2016 and 2017, we sampled six lakes with declining trends in natural Walleye recruitment (D-NR lakes) and seven lakes with a history of sustained natural recruitment (S-NR lakes) to determine if timing of potential recruitment bottlenecks for age-0 Walleye were consistent among D-NR lakes and if abiotic and biotic metrics differed between D-NR and S-NR lakes. We also examined diets of larval Walleye to assess prey items that may be important to early growth and survival and to determine if occurrence of piscivory was related to larval Walleye total length. Differential patterns in the presence and absence of age-0 Walleye at different life history stages in the first 6 months of life suggested that recruitment bottlenecks in D-NR lakes were consistently occurring before mid-July (five of six lakes). Mean Secchi depth, surface conductivity, abundance of larval Yellow Perch Perca flavescens, and most metrics of zooplankton abundance and mean size were similar between D-NR and S-NR lakes. Log10 transformed number of adult Walleye per hectare was lower and adult mean total length was higher in D-NR lakes. Across all lakes, diets of larval Walleye consisted of zooplankton and larval fish and the occurrence of piscivory was higher than reported in previous studies and was positively related to total length of larval Walleye. Causes of recruitment bottlenecks in D-NR lakes remain unclear, making it difficult to identify management actions that might be implemented to circumvent these bottlenecks. However, our results indicate that future research should focus on the period between egg deposition and mid-July.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10683","usgsCitation":"Gostiaux, J., Boehm, H.I., Jaksha, N.J., Dembkowski, D., Hennessy, J.M., and Isermann, D.A., 2022, Recruitment bottlenecks for age-0 walleye in northern Wisconsin lakes: North American Journal of Fisheries Management, v. 42, no. 3, p. 507-522, https://doi.org/10.1002/nafm.10683.","productDescription":"16 p.","startPage":"507","endPage":"522","ipdsId":"IP-127091","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":397234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.74658203125,\n 45.08127861241874\n ],\n [\n -87.879638671875,\n 44.80132682904856\n ],\n [\n -87.9345703125,\n 45.644768217751924\n ],\n [\n -90.142822265625,\n 46.35451083736523\n ],\n [\n -90.71411132812499,\n 46.65697731621612\n ],\n [\n -90.95581054687499,\n 46.604167162931844\n ],\n [\n -90.758056640625,\n 46.94276208682137\n ],\n [\n -90.933837890625,\n 46.97275640318636\n ],\n [\n -92.010498046875,\n 46.70973594407157\n ],\n [\n -92.74658203125,\n 45.08127861241874\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-10-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Gostiaux, Jason","contributorId":288755,"corporation":false,"usgs":false,"family":"Gostiaux","given":"Jason","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":838263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boehm, Hadley I. A.","contributorId":288756,"corporation":false,"usgs":false,"family":"Boehm","given":"Hadley","email":"","middleInitial":"I. A.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":838264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaksha, Nathan J.","contributorId":288757,"corporation":false,"usgs":false,"family":"Jaksha","given":"Nathan","email":"","middleInitial":"J.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":838265,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dembkowski, Daniel J.","contributorId":288759,"corporation":false,"usgs":false,"family":"Dembkowski","given":"Daniel J.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":838266,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hennessy, Joseph M.","contributorId":288761,"corporation":false,"usgs":false,"family":"Hennessy","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":838267,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":838262,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70225745,"text":"70225745 - 2022 - Activity-based, genome-resolved metagenomics uncovers key populations and pathways involved in subsurface conversions of coal to methane","interactions":[],"lastModifiedDate":"2022-03-28T16:03:16.089871","indexId":"70225745","displayToPublicDate":"2021-10-21T08:26:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3563,"text":"The ISME Journal","active":true,"publicationSubtype":{"id":10}},"title":"Activity-based, genome-resolved metagenomics uncovers key populations and pathways involved in subsurface conversions of coal to methane","docAbstract":"Microbial metabolisms and interactions that facilitate subsurface conversions of recalcitrant carbon to methane are poorly understood. We deployed an in situ enrichment device in a subsurface coal seam in the Powder River Basin (PRB), USA, and used BONCAT-FACS-Metagenomics to identify translationally active populations involved in methane generation from a variety of coal-derived aromatic hydrocarbons. From the active fraction, high-quality metagenome-assembled genomes (MAGs) were recovered for the acetoclastic methanogen, Methanothrix paradoxum, and a novel member of the Chlorobi with the potential to generate acetate via the Pta-Ack pathway. Members of the Bacteroides and Geobacter also encoded Pta-Ack and together, all four populations had the putative ability to degrade ethylbenzene, phenylphosphate, phenylethanol, toluene, xylene, and phenol. Metabolic reconstructions, gene analyses, and environmental parameters also indicated that redox fluctuations likely promote facultative energy metabolisms in the coal seam. The active “Chlorobi PRB” MAG encoded enzymes for fermentation, nitrate reduction, and multiple oxygenases with varying binding affinities for oxygen. “M. paradoxum PRB” encoded an extradiol dioxygenase for aerobic phenylacetate degradation, which was also present in previously published Methanothrix genomes. These observations outline underlying processes for bio-methane from subbituminous coal by translationally active populations and demonstrate activity-based metagenomics as a powerful strategy in next generation physiology to understand ecologically relevant microbial populations.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41396-021-01139-x","usgsCitation":"McKay, L.J., Smith, H.J., Barnhart, E.P., Schweitzer, H.S., Malmstrom, R.R., Goudeau, D., and Fields, M.W., 2022, Activity-based, genome-resolved metagenomics uncovers key populations and pathways involved in subsurface conversions of coal to methane: The ISME Journal, v. 16, p. 915-926, https://doi.org/10.1038/s41396-021-01139-x.","productDescription":"12 p.","startPage":"915","endPage":"926","ipdsId":"IP-126752","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":449609,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41396-021-01139-x","text":"Publisher Index Page"},{"id":391508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","otherGeospatial":"Powder River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.75439453125,\n 41.409775832009565\n ],\n [\n -104.765625,\n 41.83682786072714\n ],\n [\n -104.23828125,\n 44.59046718130883\n ],\n [\n -104.9853515625,\n 46.649436163350245\n ],\n [\n -106.58935546875,\n 46.7549166192819\n ],\n [\n -108.1494140625,\n 46.51351558059737\n ],\n [\n -108.12744140625,\n 45.38301927899065\n ],\n [\n -106.41357421875,\n 43.6599240747891\n ],\n [\n -105.99609375,\n 41.83682786072714\n ],\n [\n -105.75439453125,\n 41.409775832009565\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2021-10-23","publicationStatus":"PW","contributors":{"authors":[{"text":"McKay, Luke J.","contributorId":268349,"corporation":false,"usgs":false,"family":"McKay","given":"Luke","email":"","middleInitial":"J.","affiliations":[{"id":55631,"text":"Center for Biofilm Engineering, Montana State University, Bozeman","active":true,"usgs":false}],"preferred":false,"id":826471,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Heidi J.","contributorId":268344,"corporation":false,"usgs":false,"family":"Smith","given":"Heidi","email":"","middleInitial":"J.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":826472,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnhart, Elliott P. 0000-0002-8788-8393","orcid":"https://orcid.org/0000-0002-8788-8393","contributorId":203225,"corporation":false,"usgs":true,"family":"Barnhart","given":"Elliott","middleInitial":"P.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826473,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schweitzer, Hannah S.","contributorId":268345,"corporation":false,"usgs":false,"family":"Schweitzer","given":"Hannah","email":"","middleInitial":"S.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":826474,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Malmstrom, Rex R.","contributorId":268350,"corporation":false,"usgs":false,"family":"Malmstrom","given":"Rex","email":"","middleInitial":"R.","affiliations":[{"id":55632,"text":"DOE Joint Genome Institute","active":true,"usgs":false}],"preferred":false,"id":826475,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goudeau, Danielle","contributorId":268351,"corporation":false,"usgs":false,"family":"Goudeau","given":"Danielle","email":"","affiliations":[{"id":55632,"text":"DOE Joint Genome Institute","active":true,"usgs":false}],"preferred":false,"id":826476,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fields, Matthew W.","contributorId":172391,"corporation":false,"usgs":false,"family":"Fields","given":"Matthew","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":826479,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70225520,"text":"70225520 - 2022 - Density structure of the island of Hawai’i and the implications for gravity-driven motion of the south flank of Kilauea volcano","interactions":[],"lastModifiedDate":"2021-12-10T17:03:53.974623","indexId":"70225520","displayToPublicDate":"2021-10-20T09:43:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Density structure of the island of Hawai’i and the implications for gravity-driven motion of the south flank of Kīlauea volcano","title":"Density structure of the island of Hawai’i and the implications for gravity-driven motion of the south flank of Kilauea volcano","docAbstract":"The discovery that large landslides dissected the Hawaiian islands, scattering debris over thousands of square kilometers of seafloor, changed our ideas of island growth and evolution. The evidence is consistent with catastrophic flank collapse during volcano growth, and draws our focus to the currently active island of Hawai’i, the volcanoes Mauna Loa and Kīlauea, and particularly to the actively-mobile south flank of Kīlauea volcano. Both the weight distribution and pressure within an extensive magma system are perceived to affect stability, but the role of gravitational body forces and island density distribution has not been quantitatively assessed. We use seismic velocities derived from tomography to model the density distribution of the island of Hawai’i and find that olivine-rich melts and rocks in Hawaiian volcanoes result in a close association of seismic velocity and density. The resultant density model reproduces more than 95% of the observed gravity disturbance signal wherever tomographic control exists and provides a basis for evaluating the body forces from gravity. We also find that if the decollement is weak, then gravitational body forces can produce slip that explains most seismo-tectonic and volcano-tectonic structural features of Kīlauea volcano. Where the decollement is in a state of incipient slip from this weight distribution, fluctuations in magma pressure can trigger accelerated slip on the decollement. Yet this is only true of the south flank of Kīlauea volcano. Though weight and magma distributions produce significant forces driving the west flank of Mauna Loa seaward, this flank is stable. Stability over the last decade indicates a strong foundation beneath the west flank of Mauna Loa, perhaps as a result of large debris avalanches that occurred there that scraped clay-rich sediments off of the decollement.","language":"English","publisher":"Oxford University Press","doi":"10.1093/gji/ggab398","usgsCitation":"Denlinger, R.P., and Flinders, A.F., 2022, Density structure of the island of Hawai’i and the implications for gravity-driven motion of the south flank of Kilauea volcano: Geophysical Journal International, v. 228, no. 3, p. 1793-1807, https://doi.org/10.1093/gji/ggab398.","productDescription":"15 p.","startPage":"1793","endPage":"1807","ipdsId":"IP-126754","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":449612,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggab398","text":"Publisher Index Page"},{"id":390674,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mount Kīlauea, Mount Mauna Loa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.6597900390625,\n 18.87510275035649\n ],\n [\n -155.50048828125,\n 19.108838815166006\n ],\n [\n -155.26153564453125,\n 19.251515342943254\n ],\n [\n -155.15441894531247,\n 19.233363381183896\n ],\n [\n -154.940185546875,\n 19.32669491605546\n ],\n [\n -154.77813720703125,\n 19.497664168139053\n ],\n [\n -154.80010986328125,\n 19.54426088484117\n ],\n [\n -154.96490478515625,\n 19.645174265699062\n ],\n [\n -154.97589111328125,\n 19.74343913716519\n ],\n [\n -155.07476806640625,\n 19.748609300218842\n ],\n [\n -155.08026123046875,\n 19.815806165386956\n ],\n [\n -155.0665283203125,\n 19.87522588708924\n ],\n [\n -155.26702880859375,\n 20.037870053952016\n ],\n [\n -155.48126220703125,\n 20.125576455270572\n ],\n [\n -155.56365966796875,\n 20.146206116089946\n ],\n [\n -155.59112548828122,\n 20.135891626114574\n ],\n [\n -155.753173828125,\n 20.259620485824865\n ],\n [\n -155.89599609375,\n 20.287961155077717\n ],\n [\n -155.91796874999997,\n 20.246736652244206\n ],\n [\n -155.92620849609375,\n 20.16425483433661\n ],\n [\n -155.84106445312497,\n 20.014645445341365\n ],\n [\n -155.91522216796875,\n 19.94236918954201\n ],\n [\n -155.94268798828125,\n 19.87005983797396\n ],\n [\n -155.99761962890625,\n 19.85714397875396\n ],\n [\n -156.0882568359375,\n 19.748609300218842\n ],\n [\n -155.906982421875,\n 19.295590314804254\n ],\n [\n -155.93719482421875,\n 19.134789188332523\n ],\n [\n -155.92620849609375,\n 19.05173366503917\n ],\n [\n -155.6597900390625,\n 18.87510275035649\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"228","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Denlinger, Roger P. 0000-0003-0930-0635 roger@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-0635","contributorId":2679,"corporation":false,"usgs":true,"family":"Denlinger","given":"Roger","email":"roger@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":825398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flinders, Ashton F. 0000-0003-2483-4635 aflinders@usgs.gov","orcid":"https://orcid.org/0000-0003-2483-4635","contributorId":196960,"corporation":false,"usgs":true,"family":"Flinders","given":"Ashton","email":"aflinders@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":153,"text":"California Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":825399,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70225562,"text":"70225562 - 2022 - Modeling seismic network detection thresholds using production picking algorithms","interactions":[],"lastModifiedDate":"2022-01-06T17:27:19.306006","indexId":"70225562","displayToPublicDate":"2021-10-20T05:53:41","publicationYear":"2022","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":"Modeling seismic network detection thresholds using production picking algorithms","docAbstract":"Estimating the detection threshold of a seismic network (the minimum magnitude earthquake that can be reliably located) is a critical part of network design and can drive network maintenance efforts. The ability of a station to detect an earthquake is often estimated by assuming the spectral amplitude for an earthquake of a given size, assuming an attenuation relationship, and comparing the predicted amplitude with the average station background noise level. This approach has significant uncertainty because of unknown regional attenuation and complications in computing small event power spectra, and it fails to account for the specific capabilities of the automatic seismic phase picker used in monitoring. We develop a data‐driven approach to determine network detection thresholds using a multiband phase picking algorithm that is currently in use at the U.S. Geological Survey National Earthquake Information Center. We apply this picking algorithm to cataloged earthquakes to determine an empirical relationship of the observability of earthquakes as a function of magnitude and distance. Using this relationship, we produce maps of detection threshold using station spatial configuration and station noise levels. We show that quiet, well‐sited stations significantly increase the detection capabilities of a network compared with a network composed of many noisy stations. Because our method is data driven, it has two distinct advantages: (1) it is less dependent on theoretical assumptions of source spectra and models of regional attenuation, and (2) it can easily be applied to any seismic network. This tool allows for an objective approach to the management of stations in regional seismic networks.
Worldwide, many productive rivers are dam-regulated and rely on flow management strategies that must balance support of ecological processes with human water use. One component of evaluating this balance is to understand ecological consequences of alternative flow management strategies, which has often been accomplished by coupling population dynamics models with models that relate streamflow to habitat availability and quality. Numerous methods assign habitat availability to locations within a river basin: These include fine-scale field-measured values that are extrapolated to other locations within the basin having similar physical characteristics or equation-driven values created by functions of model-predicted values of physical characteristics. The array of options for creating habitat models is evolving rapidly as high-resolution remote-sensing data becomes more accessible and computational capacity improves. Our objective was to identify trade-offs among approaches that assign habitat relationships to large rivers and to create a decision support tool to supplement choices of extent and granularity. Using a selection of case studies that represent a breadth of scales and diverse trade-offs, we demonstrate the need for a transparent process of data evaluation and assessment to determine the appropriate fit for model scope or context that best supports management needs and recognize sources of uncertainty. The structured approach proposed here aims at improving future model development and refine population dynamics models that inform the management of rivers.
Agent-based models (ABMs) and state-and-transition simulation models (STSMs) have proven useful for understanding processes underlying social-ecological systems and evaluating practical questions about how systems might respond to different scenarios. ABMs can simulate a variety of agents (autonomous units, such as wildlife or people); agent characteristics, decision-making, adaptive behavior, and mobility; and agent-environment interactions. STSMs are flexible and intuitive stochastic landscape models that can track scenarios and integrate diverse data. Both can be run spatially and track metrics of management success.
Due to the complementarity of these approaches, we sought to couple them through a dynamic linkage and demonstrate the relevance of this advancement for modeling landscape processes and patterns.
We developed analytical techniques and software tools to couple these modeling approaches using NetLogo, R, and the ST-Sim package for SyncroSim. We demonstrated the capabilities and value of this coupled approach through a proof-of-concept case study of bison-vegetation interactions in Badlands National Park.
The coupled ABM-STSM: (1) streamlined handling of model inputs and outputs; (2) allowed representation of processes at multiple temporal scales; (3) minimized assumptions; and (4) generated spatial and temporal patterns that better reflected agent-environment interactions.
These developments constitute a new approach for representing agent-environment feedbacks; modelers can now use output from an ABM to dictate landscape changes within an STSM that in turn influence agents. This facilitates experimentation across domains (agent and environment) and creation of more realistic and management-relevant projections, and opens new opportunities for communicating models and linking to other methods.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-021-01282-y","usgsCitation":"Miller, B.W., and Frid, L., 2022, A new approach for representing agent-environment feedbacks: Coupled agent-based and state-and-transition simulation models: Landscape Ecology, v. 37, p. 43-58, https://doi.org/10.1007/s10980-021-01282-y.","productDescription":"16 p.","startPage":"43","endPage":"58","ipdsId":"IP-119604","costCenters":[{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":436047,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R98PPB","text":"USGS data release","linkHelpText":"Coupled Agent-Based and State-and-Transition Simulation Model"},{"id":390809,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","noUsgsAuthors":false,"publicationDate":"2021-10-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Brian W. 0000-0003-1716-1161","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":196603,"corporation":false,"usgs":true,"family":"Miller","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":825579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frid, Leonardo","contributorId":196604,"corporation":false,"usgs":false,"family":"Frid","given":"Leonardo","email":"","affiliations":[],"preferred":false,"id":825580,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227726,"text":"70227726 - 2022 - Can the impact of canopy trees on soil and understory be altered using litter additions?","interactions":[],"lastModifiedDate":"2022-01-27T12:45:13.28956","indexId":"70227726","displayToPublicDate":"2021-10-17T06:43:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Can the impact of canopy trees on soil and understory be altered using litter additions?","docAbstract":"Trees can have large effects on soil nutrients in ways that alter succession, particularly in the case of nitrogen-(N)-fixing trees. In Hawaiʻi, forest restoration relies heavily on use of a native N-fixing tree, Acacia koa (koa), but this species increases soil-available N and likely facilitates competitive dominance of exotic pasture grasses. In contrast, Metrosideros polymorpha (‘ōhi‘a), the dominant native tree in Hawaiʻi, is less often planted because it is slow growing; yet it is typically associated with lower soil N and grass biomass, and greater native understory recruitment. We experimentally tested whether it is possible to reverse high soil N under koa by adding ‘ōhi‘a litter, using additions of koa litter or no litter as controls, over 2.5 yr. We then quantified natural litterfall and decomposition rates of ‘ōhi‘a and koa litter to place litter additions in perspective. Finally, we quantified whether litter additions altered grass biomass and if this had effects on native outplants. Adding ‘ōhi‘a litter increased soil carbon, but increased rather than decreased inorganic soil N pools. Contrary to expectations, koa litter decomposed more slowly than ‘ōhi‘a, although it released more N per unit of litter. We saw no reduction in grass biomass due to ‘ōhi‘a litter addition, and no change in native outplanted understory survival or growth. We conclude that the high N soil conditions under koa are difficult to reverse. However, we also found that outplanted native woody species were able to decrease exotic grass biomass over time, regardless of the litter environment, making this a better strategy for lowering exotic species impacts.
Long-distance migratory species often include multiple breeding populations, with distinct migration routes, wintering areas and annual-cycle timing. Detailed knowledge on population structure and migratory connectivity provides the basis for studies on the evolution of migration strategies and for species conservation. Currently, five subspecies of Bar-tailed Godwits Limosa lapponica have been described. However, with two apparently separate breeding and wintering areas, the taxonomic status of the subspecies L. l. taymyrensis remains unclear. Here we compare taymyrensis Bar-tailed Godwits wintering in the Middle East and West Africa, respectively, with respect to migration behaviour, breeding area, morphology and population genetic differentation in mitochondrial DNA. By tracking 52 individuals from wintering and staging areas over multiple years, we show that Bar-tailed Godwits wintering in the Middle East bred on the northern West-Siberian Plain (n = 19), whilst birds from West Africa bred further east, mostly on the Taimyr Peninsula (n = 12). The two groups differed significantly in body size and shape, and also in the timing of both northward and southward migrations. However, they were not genetically differentiated, indicating that the phenotypic (i.e. geographic, morphological and phenological) differences arose either very recently or without current reproductive isolation. We conclude that the taymyrensis taxon consists of two distinct populations with mostly non-overlapping flyways, which warrant treatment as separate taxonomic units. We thus propose to distinguish a more narrowly defined taymyrensis subspecies (i.e. the Bar-tailed Godwits wintering in West Africa and breeding on Taimyr), from a new yamalensis subspecies (i.e. the birds wintering in the Middle East and breeding on the northern West-Siberian Plain).
Brush piles (i.e., trees and large woody debris) are often installed in reservoirs to supplement fish habitat. The retention and dimensional change of brush piles after installation is important information that can be used to maximize the effectiveness of this management action. We evaluated the retention and dimensional change of 70 eastern red cedar Juniperus virginiana and bald cypress Taxodium distichum brush piles in an embayment of a drawdown reservoir up to four annual cycles of submergence and exposure. We used satellite imagery to supplement our onsite measurements of retention. We also examined spatial patterns of brush pile retention and dimensional change. Brush piles were lost at 10% per year, and their volume was lost at 14% per year. We compared our rates of brush pile retention and dimensional change with those from a holdout data set of 50 brush piles. Estimates between data sets did not differ statistically. Spatial patterns of retention and dimensional change coincided with morphological features in our study area, suggesting that retention and dimensional change is influenced by variable physical forces (e.g., wave action and flow) at installation locations. Our estimates of brush pile retention and dimensional change can be used to generally sustain desirable brush densities. For example, to maintain a fixed total volume of brush in our study embayment, roughly 23% of the total brush volume installed would need to be replaced annually. Similar research in reservoirs managed for other purposes is needed, as length and cycle of inundation could lead to variable rates of retention and dimensional change. Additionally, advancements into computer-assisted detection and volume estimation could reduce the time and effort needed to monitor brush piles.
","language":"English","publisher":"U.S. Fish & Wildlife Service","doi":"10.3996/JFWM-21-033","usgsCitation":"Aldridge, C., Norris, D., Hatcher, H., Coppola, G., Colvin, M., and Miranda, L.E., 2022, Retention and dimensional changes of evergreen brush piles within a flood control reservoir: Journal of Fish and Wildlife Management, v. 13, no. 1, p. 223-235, https://doi.org/10.3996/JFWM-21-033.","productDescription":"13 p.","startPage":"223","endPage":"235","ipdsId":"IP-119765","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":449622,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-033","text":"Publisher Index Page"},{"id":433459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Long Branch Creek embayment of Enid Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.84895707764991,\n 34.12639444197403\n ],\n [\n -89.84895707764991,\n 34.10300231952699\n ],\n [\n -89.8179302628156,\n 34.10300231952699\n ],\n [\n -89.8179302628156,\n 34.12639444197403\n ],\n [\n -89.84895707764991,\n 34.12639444197403\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Aldridge, C.A.","contributorId":275883,"corporation":false,"usgs":false,"family":"Aldridge","given":"C.A.","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":908887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norris, D.M.","contributorId":341780,"corporation":false,"usgs":false,"family":"Norris","given":"D.M.","email":"","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":908888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hatcher, H.R.","contributorId":278602,"corporation":false,"usgs":false,"family":"Hatcher","given":"H.R.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":908889,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coppola, G.","contributorId":265335,"corporation":false,"usgs":false,"family":"Coppola","given":"G.","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":908890,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colvin, M.E.","contributorId":341781,"corporation":false,"usgs":false,"family":"Colvin","given":"M.E.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":908891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908892,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70230025,"text":"70230025 - 2022 - Joint effects of climate, tree size, and year on annual tree growth derived using tree-ring records of ten globally distributed forests","interactions":[],"lastModifiedDate":"2022-03-25T13:43:11.24047","indexId":"70230025","displayToPublicDate":"2021-10-15T10:55:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Joint effects of climate, tree size, and year on annual tree growth derived using tree-ring records of ten globally distributed forests","docAbstract":"Tree rings provide an invaluable long-term record for understanding how climate and other drivers shape tree growth and forest productivity. However, conventional tree-ring analysis methods were not designed to simultaneously account for the effects of climate, tree size, and other drivers on individual growth, which has limited the potential to use tree rings to understand forest productivity, its climate sensitivity, and its global change responses. Here, we develop and apply a new method to simultaneously model non-linear effects of primary climate drivers, reconstructed tree diameter (DBH), and year in generalized least squares models that account for the temporal autocorrelation inherent to each individual tree’s growth. We analyze data from 3811 trees representing 40 species at 10 globally distributed sites, showing that precipitation, temperature, DBH, and calendar year have additively, and often interactively, influenced annual growth over the past 120 years. Growth responses were predominantly positive to precipitation (usually over ≥ 3-month seasonal windows) and negative to temperature (usually over ≤ 3-month seasonal windows), with both included in 78% of top models, and with non-linear responses prevalent (63% of relationships). Climate sensitivity commonly varied with DBH (44% of cases tested). Trends in ring width at small DBH were linked to the light environment under which trees established, but basal area or biomass increments consistently peaked at intermediate DBH and declined thereafter. Accounting for climate and DBH, growth rate declined over time for 92% of species in secondary or disturbed stands, whereas growth trends were mixed in older forests. These trends were largely attributable to stand dynamics as cohorts and stands age, which remain challenging to disentangle from global change drivers. By providing a parsimonious approach for characterizing multiple interacting drivers of tree growth, our method reveals a more complete picture of the factors influencing growth than has previously been possible.","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15934","usgsCitation":"Anderson-Teixeira, K.J., Herrmann, V., Rollinson, C., Gonzales, B., Gonzalez-Akre, E.B., Pederson, N., Alexander, M.R., Allen, C., Alfaro-Sanchez, R., Awada, T., Baltzer, J.L., Baker, P.J., Birch, J.D., Bunyavejchewin, S., Cherubini, P., Davies, S.J., Dow, C., Helcoski, R., Kaspar, J., Lutz, J.A., Margolis, E.Q., Maxwell, J., McMahon, S.M., Piponiot, C., Russo, S.E., Šamonil, P., Sniderhan, A.E., Tepley, A.J., Vasickova, I., Vlam, M., and Zuidema, P.A., 2022, Joint effects of climate, tree size, and year on annual tree growth derived using tree-ring records of ten globally distributed forests: Global Change Biology, v. 28, p. 245-266, https://doi.org/10.1111/gcb.15934.","productDescription":"21 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