Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favorability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. Finally, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future assessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.
Stream temperature is a fundamental control on ecosystem health. Recent efforts incorporating process guidance into deep learning models for predicting stream temperature have been shown to outperform existing statistical and physical models. This performance is in part because deep learning architectures can actively learn spatiotemporal relationships that govern how water and energy propagate through a river network. However, exploration of how spatiotemporal awareness and process guidance influence a model's generalizability under shifting environmental conditions such as climate change is limited. Here, we use Explainable Artificial Intelligence (XAI) to interrogate how differing deep learning architectures affect a model's learned spatial and temporal dependencies, and how those learned dependencies affect a model's ability to maintain high accuracy when applied to unseen environmental conditions. Using the Delaware River Basin in the northeastern United States as a test case, we compare two spatiotemporally aware process-guided deep learning models for predicting stream temperature (a recurrent graph convolution network—RGCN, and a temporal convolution graph model—Graph WaveNet). Both models achieve equally high predictive performance when testing data are well represented in the training data (test root mean squared errors of 1.64°C and 1.65°C); however, Graph WaveNet significantly outperforms RGCN in 4 out of 5 experiments where test partitions represent different types of unseen environmental conditions. XAI results show that the architecture of Graph WaveNet leads to learned spatial relationships with greater fidelity to physical processes, and that this fidelity improves the generalizability of the model when applied to shifting and/or unseen environmental conditions.
Addressing ecosystem degradation in the Anthropocene will require ecological restoration across large spatial extents. Identifying areas where natural regeneration will occur without direct resource investment will improve scalability of restoration actions.
An ecoregion in need of large scale restoration is the Great Basin of the Western US, where increasingly large and frequent wildfires threaten ecosystem integrity and its foundational shrub species. We develop a framework to forecast where post-wildfire regeneration of sagebrush cover (Artemisia spp.) is likely to occur within the burnt areas across the region (> 900,000 km2).
First, we parameterized population models using Landsat satellite-derived time series of sagebrush cover. Second, we evaluated the out-of-sample performance by predicting natural regeneration in wildfires not used for model training. This model assessment reproduces a management-oriented scenario: making restoration decisions shortly after wildfires with minimal local information. Third, we asked how accounting for increasingly fine-scale spatial heterogeneity could improve model forecasting accuracy.
Regional-level models revealed that sagebrush post-fire recovery is slow, estimating > 80-year time horizon to reach an average cover at equilibrium of 16.6% (CI95% 9–25). Accounting for wildfire and within-wildfire spatial heterogeneity improved out-of-sample forecasts, resulting in a mean absolute error of 3.5 ± 4.3% cover, compared to the regional model with an error of 7.2 ± 5.1% cover.
We demonstrate that combining population models and non-parametric spatial matching provides a flexible framework for forecasting plant population recovery. Models for population recovery applied to Landsat-derived time series will assist restoration decision-making, including identifying priority targets for restoration.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-023-01621-1","usgsCitation":"Zaiats, A., Cattau, M.E., Pilliod, D., Rongsong, L., Requena-Mullor, J.M., and Caughlin, T., 2023, Forecasting natural regeneration of sagebrush after wildfires using population models and spatial matching: Landscape Ecology, v. 38, https://doi.org/10.1007/s10980-023-01621-1.","productDescription":"16 p.","startPage":"1306","ipdsId":"IP-144778","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":414693,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.76040258225669,\n 42.96440805189778\n ],\n [\n -120.76040258225669,\n 35.34764677083406\n ],\n [\n -112.15082482848379,\n 35.34764677083406\n ],\n [\n -112.15082482848379,\n 42.96440805189778\n ],\n [\n -120.76040258225669,\n 42.96440805189778\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"38","edition":"1291","noUsgsAuthors":false,"publicationDate":"2023-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Zaiats, Andrii","contributorId":257073,"corporation":false,"usgs":false,"family":"Zaiats","given":"Andrii","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":867434,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cattau, Megan E 0000-0003-2164-3809","orcid":"https://orcid.org/0000-0003-2164-3809","contributorId":295715,"corporation":false,"usgs":false,"family":"Cattau","given":"Megan","email":"","middleInitial":"E","affiliations":[{"id":63922,"text":"Department of Human-Environment Systems, Boise State University","active":true,"usgs":false}],"preferred":false,"id":867435,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":229349,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":867436,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rongsong, Liu","contributorId":303384,"corporation":false,"usgs":false,"family":"Rongsong","given":"Liu","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":867437,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Requena-Mullor, Juan M.","contributorId":218132,"corporation":false,"usgs":false,"family":"Requena-Mullor","given":"Juan","email":"","middleInitial":"M.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":867438,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caughlin, Trevor 0000-0001-6752-2055","orcid":"https://orcid.org/0000-0001-6752-2055","contributorId":256964,"corporation":false,"usgs":false,"family":"Caughlin","given":"Trevor","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":867439,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70248732,"text":"70248732 - 2023 - Migrating ducks and submersed aquatic vegetation respond positively after invasive common carp (Cyprinus carpio) exclusion from a freshwater coastal marsh","interactions":[],"lastModifiedDate":"2023-09-19T12:03:30.238894","indexId":"70248732","displayToPublicDate":"2023-03-13T07:01:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Migrating ducks and submersed aquatic vegetation respond positively after invasive common carp (Cyprinus carpio) exclusion from a freshwater coastal marsh","docAbstract":"Invasive carp can negatively affect waterbirds through habitat degradation, including removal of submersed aquatic vegetation (SAV). At a freshwater coastal marsh of great ecological and cultural significance, we excluded invasive common carp (Cyprinus carpio) with the goal of restoring the marsh to historical conditions to support fall-migrating waterfowl. We used a multi-pronged approach to assess the response of ducks and SAV to carp exclusion by leveraging historical duck and SAV surveys and collecting new data for six years post-exclusion on density and distribution of ducks within the marsh, SAV response, and refueling performance (as indexed by plasma-lipid metabolites) by two species of diving ducks. We found that fall-migrating duck numbers and total SAV extent rebounded to historical levels (1970s). There was a 339% increase in diving duck density and a nearly 400% increase in dabbling duck density between the pre- (i.e., 2000s) and post-exclusion periods. Diving ducks were more likely to be observed associated with SAV within the marsh, whereas dabbling ducks responded to emergent vegetation extent and water levels. Refueling performance was stable post-exclusion, despite increased numbers of ducks using the marsh, indicating that marsh habitat quality was sufficient. Some aspects of the marsh recovery remain in question, including possible shifts in SAV community composition. Overall, the carp exclusion has successfully improved the quality of habitat for migrating ducks.
Wildfires pose a risk to water supplies in the western U.S. and many other parts of the world, due to the potential for degradation of water quality. However, a lack of adequate data hinders prediction and assessment of post-wildfire impacts and recovery. The dearth of such data is related to lack of funding for monitoring extreme events and the challenge of measuring the outsized hydrologic and erosive response after wildfire. Assessment and prediction of post-wildfire surface water quality would be strengthened by the strategic monitoring of key parameters, and the selection of sampling locations based on the following criteria: (1) streamgage with pre-wildfire data; (2) ability to install equipment that can measure water quality at high temporal resolution, with a focus on storm sampling; (3) minimum of 10% drainage area burned at moderate to high severity; (4) lack of major water management; (5) high-frequency precipitation; and (6) availability of pre-wildfire water-quality data and (or) water-quality data from a comparable unburned basin. Water-quality data focused on parameters that are critical to human and (or) ecosystem health, relevant to water-treatment processes and drinking-water quality, and (or) inform the role of precipitation and discharge on flow paths and water quality are most useful. We discuss strategic post-wildfire water-quality monitoring and identify opportunities for advancing assessment and prediction. Improved estimates of the magnitude, timing, and duration of post-wildfire effects on water quality would aid the water resources community prepare for and mitigate against impacts to water supplies.
Arctic marine mammals have had little exposure to vessel traffic and potential associated disturbance, but sea ice loss has increased accessibility of Arctic waters to vessels. Vessel disturbance could influence marine mammal population dynamics by altering behavioral activity budgets that affect energy balance, which in turn can affect birth and death rates. As an initial step in studying these linkages, we conducted the first comprehensive analysis to evaluate the effects of vessel exposure on Pacific walrus (Odobenus rosmarus divergens) behaviors. We obtained >120,000 h of location and behavior (foraging, in-water not foraging, and hauled out) data from 218 satellite-tagged walruses and linked them to vessel locations from the marine automatic identification system (AIS). This yielded 206 vessel-exposed walrus telemetry hours for comparison to unexposed hours, which we used to assess if vessel exposure altered walrus behavior. We developed a filter to account for misclassification of vessel exposure of telemetered walruses. Then we tested for an effect of vessel exposure on walrus behaviors using a combination of exact and propensity score-based matching to account for confounding covariates, and we conducted statistical power analyses. We did not detect an effect of vessel exposure on walrus behaviors even when statistical power was high (i.e., for foraging walruses), which may have been due to the sample size-driven need to define vessel presence within a larger than desired distance (15-km measured radius) around a walrus. Although this study did not determine at what distance vessel exposure affects walrus behaviors, it provided an upper bound on the distance at which the vessels encountered may disturb foraging walruses. When more situation-specific information is lacking, this distance could be used as a conservative buffer to maintain between vessels and areas of high use by foraging walruses. Studies on behavioral consequences of closer proximities between walruses and vessels are needed, and our assessments of misclassification rates and statistical power can be used for future studies. We demonstrated that analytical approaches such as matching, which are rarely used in wildlife studies, are particularly useful for testing hypotheses with observational data.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.4433","usgsCitation":"Taylor, R.L., Jay, C.V., Beatty, W., Fischbach, A.S., Quakenbush, L.T., and Crawford, J.A., 2023, Exploring effects of vessels on walrus behaviors using telemetry, automatic identification system data and matching: Ecosphere, v. 14, no. 3, e4433, 16 p., https://doi.org/10.1002/ecs2.4433.","productDescription":"e4433, 16 p.","ipdsId":"IP-122838","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":444233,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4433","text":"Publisher Index Page"},{"id":435414,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IO8AZJ","text":"USGS data release","linkHelpText":"Walrus Haulout and In-water Activity Levels Relative to Vessel Interactions in the Chukchi Sea, 2012-2015"},{"id":413040,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","state":"Alaska","otherGeospatial":"Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -170.32245819085716,\n 66.05513807898694\n ],\n [\n -169.7201609109013,\n 65.81337853498471\n ],\n [\n -163.44646744670234,\n 67.26413622283681\n ],\n [\n -163.48928051808477,\n 67.77761301095038\n ],\n [\n -165.89517336815703,\n 68.50009214376516\n ],\n [\n -165.8497260252095,\n 68.66729130495727\n ],\n [\n -163.80598521715572,\n 68.81337251177467\n ],\n [\n -162.7412289106771,\n 69.22689570748591\n ],\n [\n -162.42602442536432,\n 69.65754636971394\n ],\n [\n -161.76725890958286,\n 69.98451068064082\n ],\n [\n -159.03175166715397,\n 70.56710759229969\n ],\n [\n -156.4162777380868,\n 70.98318711582823\n ],\n [\n -155.2665320015126,\n 71.33015213356109\n ],\n [\n -159.80661927627526,\n 73.34469846891494\n ],\n [\n -166.5293623655165,\n 74.38868320724777\n ],\n [\n -167.6849482398208,\n 75.6045619888859\n ],\n [\n -173.68646916409662,\n 74.13834425475162\n ],\n [\n -183.01175058530794,\n 75.09322677187487\n ],\n [\n -191.7181370105502,\n 72.93563639560725\n ],\n [\n -189.31848265362305,\n 69.96553641873152\n ],\n [\n -184.14238422298672,\n 69.62713173944053\n ],\n [\n -181.59480249276817,\n 69.24919398810846\n ],\n [\n -175.799840976693,\n 67.34682708478346\n ],\n [\n -175.38326574260466,\n 66.7022806685788\n ],\n [\n -173.68704619790694,\n 65.99096338560051\n ],\n [\n -173.47219456759004,\n 66.77585470825255\n ],\n [\n -172.300442527944,\n 66.78294625934467\n ],\n [\n -170.32245819085716,\n 66.05513807898694\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":866281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":866282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beatty, William S. 0000-0003-0013-3113","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":288790,"corporation":false,"usgs":false,"family":"Beatty","given":"William S.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":866283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":2865,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony","email":"afischbach@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":866284,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quakenbush, Lori T.","contributorId":47262,"corporation":false,"usgs":true,"family":"Quakenbush","given":"Lori","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":866285,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crawford, Justin A.","contributorId":214225,"corporation":false,"usgs":false,"family":"Crawford","given":"Justin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":866286,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70241072,"text":"tm1D11 - 2023 - Field techniques for fluorescence measurements targeting dissolved organic matter, hydrocarbons, and wastewater in environmental waters: Principles and guidelines for instrument selection, operation and maintenance, quality assurance, and data reporting","interactions":[],"lastModifiedDate":"2023-04-03T16:43:31.13652","indexId":"tm1D11","displayToPublicDate":"2023-03-13T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1-D11","displayTitle":"Field Techniques for Fluorescence Measurements Targeting Dissolved Organic Matter, Hydrocarbons, and Wastewater in Environmental Waters: Principles and Guidelines for Instrument Selection, Operation and Maintenance, Quality Assurance, and Data Reporting","title":"Field techniques for fluorescence measurements targeting dissolved organic matter, hydrocarbons, and wastewater in environmental waters: Principles and guidelines for instrument selection, operation and maintenance, quality assurance, and data reporting","docAbstract":"The use of field deployable fluorescence sensors by the U.S. Geological Survey has become increasingly common for a wide variety of surface water and groundwater investigations. This report addresses field deployable fluorometers that measure the fluorescence response of various substances in water exposed to incident light generated by the sensor. An introduction to the basic principles of field measurements of fluorescence is provided, as well as technical background information on sensors that target dissolved organic matter, wastewater, and hydrocarbons, including sensor selection, operating principles, key features, and design elements. General deployment, operation and maintenance protocols, quality-assurance techniques, and suggestions for data reporting are presented to facilitate and standardize the collection and accurate communication of data collected by the U.S. Geological Survey across studies, sites, and sensor types. Sensor performance issues and common interferences are also described. An appendix is included to describe sensor calibration criteria and procedures, reporting units, and specific approaches to correct for interferences for fluorescence of dissolved organic matter sensors.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm1D11","usgsCitation":"Booth, A., Fleck, J., Pellerin, B.A., Hansen, A., Etheridge, A., Foster, G.M., Graham, J.L., Bergamaschi, B.A., Carpenter, K.D., Downing, B.D., Rounds, S.A., and Saraceno, J., 2023, Field techniques for fluorescence measurements targeting dissolved organic matter, hydrocarbons, and wastewater in environmental waters: Principles and guidelines for instrument selection, operation and maintenance, quality assurance, and data reporting: U.S. Geological Survey Techniques and Methods, book 1, chap. D11, 41 p., https://doi.org/10.3133/tm1D11.","productDescription":"Report: vi, 41 p.; Data Release","numberOfPages":"52","onlineOnly":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":414608,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm1D11/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":413883,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VJUCTP","text":"USGS data release","linkHelpText":"Comparisons from an Aqualog fluorometer standardized to quinine sulfate equivalents (QSE) with excitation (ex) and emissions (em) equivalent to fluorescence of dissolved organic Matter (fDOM) sensors from multiple manufacturers"},{"id":413879,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/01/d11/tm1d11.pdf","text":"Report","size":"3.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 1–D11"},{"id":413880,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/01/d11/tm1d11.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":413882,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/01/d11/images"},{"id":413877,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/01/d11/coverthb2.jpg"}],"contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Northern peatlands store globally-important amounts of carbon in the form of partly decomposed plant detritus. Drying associated with climate and land-use change may lead to increased fire frequency and severity in peatlands and the rapid loss of carbon to the atmosphere. However, our understanding of the patterns and drivers of peatland burning on an appropriate decadal to millennial timescale relies heavily on individual site-based reconstructions. For the first time, we synthesise peatland macrocharcoal records from across North America, Europe, and Patagonia to reveal regional variation in peatland burning during the Holocene. We used an existing database of proximal sedimentary charcoal to represent regional burning trends in the wider landscape for each region. Long-term trends in peatland burning appear to be largely climate driven, with human activities likely having an increasing influence in the late Holocene. Warmer conditions during the Holocene Thermal Maximum (∼9–6 cal. ka BP) were associated with greater peatland burning in North America's Atlantic coast, southern Scandinavia and the Baltics, and Patagonia. Since the Little Ice Age, peatland burning has declined across North America and in some areas of Europe. This decline is mirrored by a decrease in wider landscape burning in some, but not all sub-regions, linked to fire-suppression policies, and landscape fragmentation caused by agricultural expansion. Peatlands demonstrate lower susceptibility to burning than the wider landscape in several instances, probably because of autogenic processes that maintain high levels of near-surface wetness even during drought. Nonetheless, widespread drying and degradation of peatlands, particularly in Europe, has likely increased their vulnerability to burning in recent centuries. Consequently, peatland restoration efforts are important to mitigate the risk of peatland fire under a changing climate. Finally, we make recommendations for future research to improve our understanding of the controls on peatland fires.
For more than 25 years, the U.S. Geological Survey (USGS) has used the remote-sensing capabilities of United States National Imagery Systems (USNIS) to obtain high-resolution electro-optical imagery to monitor Earth’s response to global environmental change. A major focus has been monitoring sea ice behavior in the Arctic Ocean and its marginal seas. In 1997 and 1998, under the direction of the Global Fiducials Program (GFP), USNIS imagery was collected during the Surface Heat Budget of the Arctic Ocean (SHEBA) Project. In 1999, collection of USNIS imagery of six static sea ice sites in the Arctic Ocean and its marginal seas began, and the imagery was archived in the USGS-hosted Global Fiducials Library (GFL). The static sites were imaged through 2014, creating time series of geographically referenced images which scientists have used to study seasonal changes in Arctic ice over the same locations for extended time periods. In early 2009, the Central Intelligence Agency’s MEDEA Program requested that the USGS use USNIS imagery to track movements of sea ice floes during an entire Arctic summer (April through September). The goal was to improve researchers’ understanding of seasonal changes in Arctic sea ice. In order to track and repeatedly capture imagery of the same ice as it drifted across the Arctic Ocean, the USGS developed a methodology and a series of protocols to use data from telemetering drift buoys deployed at locations across the Arctic Ocean by the International Arctic Buoy Programme (IABP) to track the drift of targeted ice masses for periods that exceeded a year. Resulting time series of sea ice imagery, captured while monitoring 38 individual buoys, were archived in the GFL. In 2013 and 2014, in support of the Seasonal Ice Zone Reconnaissance Surveys (SIZRS) Program led by the University of Washington, Seattle, Washington, the USGS requested the collection of USNIS imagery of selected sites in the Beaufort and Chukchi Seas located at every degree of latitude between 70º and 80º N. along a north-south transect. This was done to track and understand the interplay among the ice, atmosphere, and ocean and what it contributes to the rapid decline in summer ice extent that has occurred in recent years. Under the auspices of the GFP, thousands of sea ice images have been collected. Many of those that pass a quality and cloud-cover screening are archived in the GFL. Of these, more than 1,750 sea ice images have been publicly released, following an editing and processing procedure that produces high-resolution degraded images, known as “literal imagery-derived products” or LIDPs. These LIDPs have been approved for free, unrestricted public distribution and scientific analysis. The LIDPs can be downloaded from the USGS Global Fiducials Library Data Access Portal (USGS GFLDAP) at https://www.usgs.gov/global-fiducials-library-data-access-portal. In addition, nonliteral imagery-derived products (nonliteral IDPs), such as metadata, maps, charts, and graphs, have also been released.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231008","usgsCitation":"Molnia, B.F., and Wilson, E.M., 2023, Documenting Arctic sea ice dynamics with Global Fiducials Program imagery: U.S. Geological Survey Open-File Report 2023–1008, 32 p., https://doi.org/10.3133/ofr20231008.","productDescription":"viii, 32 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-129958","costCenters":[{"id":36171,"text":"National Civil Applications Center","active":true,"usgs":true}],"links":[{"id":499733,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114471.htm","linkFileType":{"id":5,"text":"html"}},{"id":413704,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1008/images/"},{"id":413703,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1008/ofr20231008.XML"},{"id":413702,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231008/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1008"},{"id":413701,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1008/ofr20231008.pdf","text":"Report","size":"37.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1008"},{"id":413700,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1008/coverthb.jpg"}],"contact":"Director, National Civil Applications Center
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 562
Reston, VA 20192
Email: cac@usgs.gov
The reproductive ecology of geese that breed in the Arctic and subarctic is likely susceptible to the effects of climate change, which is projected to alter the environmental conditions of northern latitudes. Nest survival is an important component of productivity in geese; however, the effects of regional environmental conditions on nest survival are not well understood for some species, including the Emperor Goose (Anser canagicus), a species of conservation concern that is endemic to the Bering Sea region. We estimated nest survival and examined how indices of regional environmental conditions, nest traits (nest age, initiation date, and maximum number of eggs in the nest), and researcher disturbance influenced daily survival probability (DSP) of Emperor Goose nests using hierarchical models and 24 years of nest monitoring data (1994–2017) from the Yukon–Kuskokwim Delta (Y–K Delta) in western Alaska. Our results indicate that overall nest survival was generally high (µ = 0.766, 95% CRI: 0.655–0.849) and ranged from 0.327 (95% CRI: 0.176–0.482) in 2013 to 0.905 (95% CRI: 0.839–0.953) in 1995. We found that DSPs of nests were influenced by nest traits, negatively influenced by major tidal flooding events and by researcher disturbance, but were not influenced by regional indices of spring timing, temperature and precipitation during nesting, or fox and vole abundance on the Y–K Delta. However, the number of nests found each year was negatively related to our index of fox abundance, suggesting nests that failed as a result of fox predation may have never been discovered due to our limited nest-searching efforts during egg laying. Our results suggest that regional environmental variation had minimal influence on the nest survival of Emperor Geese, although major flooding events were important. Nevertheless, we suspect that within-year variation in local weather conditions and local abundance of predators and alternative prey may be important and should be considered in future studies.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duad008","usgsCitation":"Thompson, J.M., Uher-Koch, B.D., Daniels, B.L., Schmutz, J.A., and Sedinger, B.S., 2023, Nest traits and major flooding events influence nest survival of Emperor Geese while regional environmental variation linked to climate does not: Ornithological Applications, v. 125, no. 2, duad008, 14 p., https://doi.org/10.1093/ornithapp/duad008.","productDescription":"duad008, 14 p.","ipdsId":"IP-144477","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":444247,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1093/ornithapp/duad008","text":"Publisher Index Page"},{"id":435417,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9891BFB","text":"USGS data release","linkHelpText":"Emperor Goose (Anser canagicus) Nest Survival Encounter History from the Yukon-Kuskokwim Delta, Alaska, 1994-2017"},{"id":416853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon-Kuskokwim Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -166.0853296316241,\n 61.527680543295105\n ],\n [\n -166.0853296316241,\n 60.419454074425744\n ],\n [\n -163.581422052621,\n 60.419454074425744\n ],\n [\n -163.581422052621,\n 61.527680543295105\n ],\n [\n -166.0853296316241,\n 61.527680543295105\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"125","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, Jordan M.","contributorId":303133,"corporation":false,"usgs":false,"family":"Thompson","given":"Jordan","email":"","middleInitial":"M.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":872081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Uher-Koch, Brian D. 0000-0002-1885-0260 buher-koch@usgs.gov","orcid":"https://orcid.org/0000-0002-1885-0260","contributorId":5117,"corporation":false,"usgs":true,"family":"Uher-Koch","given":"Brian","email":"buher-koch@usgs.gov","middleInitial":"D.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":872082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daniels, Bryan L.","contributorId":304964,"corporation":false,"usgs":false,"family":"Daniels","given":"Bryan","email":"","middleInitial":"L.","affiliations":[{"id":66195,"text":"Yukon Delta National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":872083,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmutz, Joel A.","contributorId":304965,"corporation":false,"usgs":false,"family":"Schmutz","given":"Joel","email":"","middleInitial":"A.","affiliations":[{"id":66196,"text":"Alaska Science Center WTEB (retired)","active":true,"usgs":false}],"preferred":false,"id":872084,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sedinger, Benjamin S.","contributorId":304966,"corporation":false,"usgs":false,"family":"Sedinger","given":"Benjamin","email":"","middleInitial":"S.","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":872085,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70241155,"text":"70241155 - 2023 - Wastewater reuse and predicted ecological risk posed by contaminant mixtures in Potomac River watershed streams","interactions":[],"lastModifiedDate":"2023-08-07T17:00:33.651676","indexId":"70241155","displayToPublicDate":"2023-03-10T06:58:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Wastewater reuse and predicted ecological risk posed by contaminant mixtures in Potomac River watershed streams","docAbstract":"A wastewater model was applied to the Potomac River watershed to provide (i) a means to identify streams with a high likelihood of carrying elevated effluent-derived contaminants and (ii) risk assessments to aquatic life and drinking water. The model linked effluent discharges along stream networks, accumulated wastewater, and predicted contaminant loads of municipal wastewater constituents while accounting for instream dilution and attenuation. Simulations using 2016 data suggested that nearly 30% (8281 km) of streams were wastewater impacted. Low- to medium-order streams had the largest range of accumulated wastewater (ACCWW%) values. ACCWW% exceeded a 1% threshold at >39% of drinking-water intakes (varied by temporal condition). Risk assessments of municipal wastewater-contaminant mixtures indicated that 22% (1479 km) of streams impacted by municipal wastewater (5.5% of all reaches modeled) may pose high risk to aquatic organisms under mean-annual conditions, with fish more susceptible to chronic-exposure effects relative to other taxa. Risk varied temporally and by stream order, with the greatest risk occurring in the summer in small streams. These findings suggest that wastewater may be an important factor contributing to environmental degradation in the Potomac River watershed.
Anthropogenically degraded benthic-macroinvertebrate communities (benthos) are one of seven beneficial use impairments (BUIs) in the Niagara River Area of Concern (AOC). Over the last 50 years, upgrades to waste-water treatment, industry closures, and sediment remediations reduced contaminant levels throughout the system. Improvements in benthic communities and sediment toxicity, however, were difficult to assess because there are no comparable reference reaches outside the AOC. A multi-phase study was initiated in 2015 to determine if data from inside the AOC could identify reference conditions, if toxicity and benthic-community data from these sites differed from other AOC sites, and if further remediation efforts were warranted in parts of the AOC. Concentrations or quotients of PAHs, PCBs, dioxins and furans, pesticides, and most metals were below their New York Sediment Class A Guidance Values at 10 sites that were subsequently designated as reference sites. Survival and growth data from Chironomus dilutus and Hyalella azteca bioassays indicated that sediments from only a few individual AOC-impact sites were toxic or significantly different from reference sites, and that mean toxicity at pooled AOC-impact and reference sites did not differ significantly. Similarly, New York Biological Assessment Profile scores and chironomid mentum deformity scores at only a few individual sites differed significantly from corresponding indices at reference sites, but neither metric differed significantly in comparisons between pooled AOC-impact and reference sites. Most analyses indicated that benthic communities were unimpaired and that removal criteria for the benthos BUI were largely met in much of the upper Niagara River AOC.
This three-dimensional (3D) geologic map displays the subsurface geology in the upper ~4 kilometers of the Earth’s crust in the southeastern Gabbs Valley geothermal area of west-central Nevada. The 3D map was constructed by integrating the results from detailed geologic mapping, 3D gravity inversion modeling, and potential-field-geophysical studies. This effort was undertaken as part of the Nevada Play Fairway Project, a regional effort to characterize new geothermal resources in the United States. Local data collection and analysis in southeastern Gabbs Valley, Nevada, including the construction of this 3D map, led to the drilling of six temperature gradient wells and identification of previously unknown hydrothermal fluids at 150 meters depth. The measured temperatures, which are as high as 124.9 degrees Celsius, indicate that the southeastern Gabbs Valley hydrothermal system has temperatures that are comparable to geothermal fields that have been developed for electricity generation in the region. We describe the geologic units and structures displayed by the map and discuss the methods used to integrate the geologic and geophysical information into the 3D geologic interpretation. The accompanying map provides horizontal and vertical section views and oblique perspective views from several angles. The digital data for elements of the map, the individual 3D fault surfaces, and stratigraphic surfaces are available from Siler (2022). The accompanying map sheet and video displaying the 3D map are available at https://doi.org/10.3133/sim3498.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3498","usgsCitation":"Siler, D.L., Witter, J.B., Craig, J.W., Earney, T.E., Schermerhorn, W.D., Fournier, D., Faulds, J.E., Glen, J.M.G., and Peacock, J.R., 2023, Three-dimensional geologic map the southeastern Gabbs Valley geothermal area, Nevada: U.S. Geological Survey Scientific Investigations Map 3498, 23 p., 1 sheet, https://doi.org/10.3133/sim3498.","productDescription":"Pamphlet: v, 23 p.; 1 Sheet: 46.00 × 39.00 inches; Video","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-122870","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":500204,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114474.htm","linkFileType":{"id":5,"text":"html"}},{"id":413934,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3498/sim3498_video.mp4","text":"Video","size":"45 MB MP4"},{"id":413933,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sim/3498/sim3498_pamphlet.pdf","text":"Pamphlet","size":"20 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":413932,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3498/sim3498_sheet.pdf","text":"Sheet","size":"25 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":413931,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3498/covrthb.jpg"},{"id":413930,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BR3681","text":"Stratigraphic and fault surfaces from the three-dimensional geologic map of the southeastern Gabbs Valley geothermal area","description":"Siler, D.L., 2022, Stratigraphic and fault surfaces from the three-dimensional geologic map of the southeastern Gabbs Valley geothermal area: U.S. Geological Survey data release, https://doi.org/10.5066/P9BR3681."}],"country":"United States","state":"Nevada","otherGeospatial":"Gabbs Valley geothermal area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.3,\n 38.3\n ],\n [\n -117.3,\n 39.0\n ],\n [\n -119.0,\n 39.0\n ],\n [\n -119.0,\n 38.3\n ],\n [\n -117.3,\n 38.3\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center Moffett Field
U.S. Geological Survey
350 N. Akron Rd. P.O. Box 158
Moffett Field, CA 94035
This report provides a summary of terrestrial invertebrates collected at old field, mature, and restored hardwood forest floodplain sites in northeast Indiana. Invertebrate populations were sampled at selected sites using walking butterfly transects, pitfall-enhanced Malaise invertebrate traps (PEMITs), and sweep nets. We identified a total of 19 taxonomic groups of butterflies, with 1, 11, and 18 groups from the old field, mature, and restored sites, respectively. Samples collected with PEMITs captured 26 different invertebrate taxa and 4 vertebrate taxa on mature and restored sites (24 invertebrate taxa, each, on mature and restored sites; 3 and 2 vertebrate species on mature and restored sites, respectively). Sweep net sampling of restored sites captured 18 invertebrate taxa, including mantids (Mantodea), which were not detected using PEMITs. These data were collected in anticipation of assessing the progress of restored hardwood forest communities towards conditions associated with mature seasonally inundated floodplain forests in northeast Indiana.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1168","usgsCitation":"Albers, J.L., Wildhaber, M.L., Struckhoff, M.A., Westrich, D.J., Green, N.S., Poulton, B.C., and Hooper, M.J., 2023, Terrestrial invertebrate diversity and occurrence in restored hardwood forest floodplains, Indiana, United States, June–August 2016: U.S. Geological Survey Data Report 1168, 7 p., https://doi.org/10.3133/dr1168.","productDescription":"Report: vi, 7 p.; Data Release","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-131446","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":413907,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YZX7G6","text":"USGS data release","linkHelpText":"Terrestrial invertebrate diversity and occurrence in restored hardwood forest floodplains, Indiana, United States, June–August 2016"},{"id":413925,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1168/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":413902,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1168/coverthb.jpg"},{"id":413904,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1168/dr1168.pdf","text":"Report","size":"2.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1168"},{"id":413905,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1168/dr1168.XML","size":"55.2 kB","linkFileType":{"id":8,"text":"xml"},"description":"DR 1168 XML"},{"id":413906,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1168/images"}],"country":"United States","state":"Indiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.05935419571834,\n 41.09321758703314\n ],\n [\n -85.05935419571834,\n 41.058939864910855\n ],\n [\n -85.01182417936363,\n 41.058939864910855\n ],\n [\n -85.01182417936363,\n 41.09321758703314\n ],\n [\n -85.05935419571834,\n 41.09321758703314\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
With viruses often having devastating effects on wildlife population fitness and wild mammals serving as pathogen reservoirs for potentially zoonotic diseases, determining the viral diversity present in wild mammals is both a conservation and One Health priority. Additionally, transmission from more abundant hosts could increase the extinction risk of threatened sympatric species. We leveraged an existing circular DNA enriched metagenomic dataset generated from bobcat (Lynx rufus, n = 9) and puma (Puma concolor, n = 13) scat samples non-invasively collected from Sonora, Mexico, to characterize fecal DNA viromes of each species and determine the extent that viruses are shared between them. Using the metaWRAP pipeline to co-assemble viral genomes for comparative metagenomic analysis, we observed diverse circular DNA viruses in both species, including circoviruses, genomoviruses, and anelloviruses. We found that differences in DNA virome composition were partly attributed to host species, although there was overlap between viruses in bobcats and pumas. Pumas exhibited greater levels of alpha diversity, possibly due to bioaccumulation of pathogens in apex predators. Shared viral taxa may reflect dietary overlap, shared environmental resources, or transmission through host interactions, although we cannot rule out species-specific host-virus coevolution for the taxa detected through co-assembly. However, our detection of integrated feline foamy virus (FFV) suggests Sonoran pumas may interact with domestic cats. Our results contribute to the growing baseline knowledge of wild felid viral diversity. Future research including samples from additional sources (e.g., prey items, tissues) may help to clarify host associations and determine the pathogenicity of detected viruses.
Winslow Township and the Camden County Municipal Utility Authority (CCMUA) developed a plan to shut down the Winslow sewage-treatment facility and associated effluent infiltration facility and transfer the effluent to the CCMUA sewage-treatment facility on the Delaware River in Camden, New Jersey. Winslow Township reduced groundwater withdrawals from the Kirkwood-Cohansey aquifer system to offset groundwater recharge lost with the cessation of effluent infiltration. The U.S. Geological Survey, in cooperation with Winslow Township and the CCMUA, collected data to evaluate conditions prior to cessation of effluent infiltration and installed two continuous-record streamflow-gaging stations. Streamflow measurements also were made at two low-flow partial-record sites, and groundwater levels were measured in 17 wells at high and low water-level periods (May and September 2010). A groundwater-flow model provides estimated changes in base flow of the Great Egg Harbor River under several groundwater-withdrawal and effluent infiltration scenarios.
Water levels were measured in an observation well 480 feet (ft) from the infiltration lagoons during 1971–2010. A downward trend in water levels in the well prior to 1985 is attributed in part to increased impervious surfaces and groundwater withdrawals associated with development in the area that began in the early 1970s. From late 1985 to 2010, there was an upward trend in water levels in the well that is attributed to the construction of nearby effluent infiltration lagoons in 1985 and the increasing rate of effluent infiltration during the period. Recent and historical measurements made at the four surface-water sites were correlated with same-day discharges measured at three nearby index stations to estimate continuous low-flow record at the sites. Effects on base flow caused by reductions in groundwater withdrawals or the cessation of effluent infiltration in Winslow Township could not be ascertained from the available data with the statistical and analysis methods used.
Groundwater discharge to streams (base flow) was simulated with a groundwater-flow model of the Great Egg Harbor and Mullica River Basins. Simulated monthly base flows using 2008–10 withdrawal rates and effluent recharge (Scenario 1) are generally about 1.5 million gallons per day (Mgal/d) greater than simulated base flows using 2003–07 withdrawal rates (Baseline Scenario) because of the 1.57 Mgal/d reduction in average withdrawals by Winslow Township from the Kirkwood-Cohansey aquifer system from 2003–07 to 2008–10. Simulated monthly base flows using 2008–10 withdrawals but without effluent infiltration (Scenario 2) are very similar to, but typically slightly lower than, Baseline Scenario base flows.
Three hypothetical future distributions of groundwater withdrawals from existing Winslow Township wells are simulated, each without effluent infiltration and using the same groundwater withdrawal rate as Scenario 2, but with different hypothetical distributions of withdrawals among existing Winslow Township wells. The Scenario 3 and 4 base flows are greater than the Baseline Scenario base flows in all months, and the Scenario 5 base flows are less than the Baseline Scenario base flows in all months. The simulation results indicate that a reduction in average withdrawals from the Kirkwood-Cohansey aquifer system by 1.57 Mgal/d offsets the reduction of effluent infiltration by about the same rate, resulting in nearly unchanged base flows in the Great Egg Harbor River near Blue Anchor (01410820).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235002","collaboration":"Prepared in cooperation with the Township of Winslow and the Camden County Municipal Utilities Authority","usgsCitation":"Carleton, G.B., and Pope, D.A., 2023, Hydrologic effects of possible changes in water-supply withdrawals from, and effluent recharge to, the Kirkwood-Cohansey aquifer system, Winslow Township, Camden County, New Jersey: U.S. Geological Survey Scientific Investigations Report 2023–5002, 16 p., https://doi.org/10.3133/sir20235002.","productDescription":"Report: vii, 16 p.; Data Release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057410","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":413542,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7154G0Z","text":"USGS data release","linkHelpText":"MODFLOW-2000 model used to evaluate the effects of possible changes in water-supply withdrawals from, and effluent recharge to, the Kirkwood-Cohansey aquifer system, Winslow Township, Camden County, New Jersey"},{"id":500487,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114441.htm","linkFileType":{"id":5,"text":"html"}},{"id":413541,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5002/images/"},{"id":413538,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5002/sir20235002.pdf","text":"Report","size":"1.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5002"},{"id":413537,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5002/coverthb.jpg"},{"id":413539,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235002/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5002"},{"id":413540,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5002/sir20235002.XML"}],"country":"United States","state":"New Jersey","county":"Camden County","otherGeospatial":"Winslow Township","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75,\n 39.833\n ],\n [\n -75,\n 39.5833\n ],\n [\n -74.833,\n 39.5833\n ],\n [\n -74.833,\n 39.833\n ],\n [\n -75,\n 39.833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ, 08648
Since the early 1900s, groundwater withdrawn from the primary aquifers that compose the Gulf Coast aquifer system—the Chicot, Evangeline, and Jasper aquifers—has been an important source of water in the greater Houston area, Texas. This report, prepared by the U.S. Geological Survey in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District, is one in an annual series of reports depicting the status of water-level altitudes and water-level changes in these aquifers in the greater Houston area.
In this report, the Chicot and Evangeline aquifers are treated as a single hydrogeologic unit for the purposes of providing annual assessments of regional-scale water-level altitudes and changes over time. In 2022, shaded depictions of water-level altitudes for the Chicot and Evangeline aquifers (undifferentiated) ranged from about 270 feet (ft) below the North American Vertical Datum of 1988 (NAVD 88) to about 195 ft above NAVD 88. The largest decline in water-level altitudes indicated by the 1977–2022 long-term water-level-change map was southeast of The Woodlands. In comparison, the 1990–2022 long-term water-level-change map depicts declines in water-level altitudes in localized areas at or near certain wells in parts of northwestern Harris County and southern Montgomery County. The largest rise in water-level altitudes for 1977–2022 was observed in a relatively large area in southeastern Harris County, whereas the largest rise in water-level altitudes for 1990–2022 was observed in a relatively small area in central Harris County. The 5-year short-term water-level-change map depicts the largest declines at three wells in northern Fort Bend County and the largest rises at five wells in southwestern and central Harris County. The 1-year short-term water-level-change map depicts the largest decline at a well in north-central Harris County and the largest rises at a well in north-central Fort Bend County and a well in southwestern Harris County.
In 2022, shaded depictions of water-level altitudes for the Jasper aquifer ranged from about 213 ft below NAVD 88 to about 285 ft above NAVD 88. The 2000–22 long-term water-level-change map depicts water-level declines throughout most of the study area where water-level-measurement data from the aquifer were collected, with the largest decline in north-central Harris County and south-central Montgomery County south of The Woodlands. The 5-year short-term water-level-change map depicts the largest decline at a well in Conroe and the largest rise at a well in south-central Montgomery County. The 1-year short-term water-level-change map depicts the largest decline at a well in south-central Montgomery County east of The Woodlands and the largest rise at a well in Conroe.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235007","collaboration":"Prepared in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District","usgsCitation":"Ramage, J.K., and Braun, C.L., 2023, Status of water-level altitudes and long-term and short-term water-level changes in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2022: U.S. Geological Survey Scientific Investigations Report 2023–5007, 26 p., https://doi.org/10.3133/sir20235007.","productDescription":"Report: v, 26 p.; 2 Data Releases; Dataset","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-144568","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":413744,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F32XDT","text":"USGS data release","linkHelpText":"Groundwater-level altitudes and long-term groundwater-level changes in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2022"},{"id":413743,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P967ZHTU","text":"USGS data release","linkHelpText":"Depth to groundwater measured from wells completed in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2022"},{"id":413745,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":413736,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5007/sir20235007.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":413852,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235007/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":413730,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5007/coverthb.jpg"},{"id":413735,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5007/sir20235007.pdf","text":"Report","size":"13.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5007"},{"id":413742,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5007/images"},{"id":500687,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114444.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Texas","city":"Houston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.20508784641805,\n 29.65321984264439\n ],\n [\n -94.58944610142002,\n 30.08175651239739\n ],\n [\n -95.09460266513673,\n 30.461126573452134\n ],\n [\n -95.76448419528316,\n 30.669153528428893\n ],\n [\n -96.01706247714125,\n 30.57465112178049\n ],\n [\n -96.32454908114292,\n 30.091258611624937\n ],\n [\n -96.14884245028512,\n 29.605491239224605\n ],\n [\n -95.84135584628345,\n 29.098182928087823\n ],\n [\n -95.29227262485227,\n 28.92531664791001\n ],\n [\n -95.0616576718509,\n 28.94453828891595\n ],\n [\n -94.87496937656448,\n 29.126965830599318\n ],\n [\n -94.58944610142002,\n 29.414351031110456\n ],\n [\n -94.19410618198944,\n 29.54818708251109\n ],\n [\n -94.20508784641805,\n 29.65321984264439\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
This report updates groundwater-storage and groundwater-level trends presented in U.S. Geological Survey (USGS) Scientific Investigations Report 2019–5060, in the Big Chino Subbasin, Yavapai County, Arizona. This earlier geophysical investigation of groundwater-storage change in the Big Chino Subbasin was conducted by the U.S. Geological Survey, in cooperation with the City of Prescott, the Town of Prescott Valley, and the Salt River Project from 2010 to 2017 to understand groundwater-level and groundwater-storage changes. Conclusions were based on precipitation, streamflow, groundwater level, and repeat microgravity data; the latter is a direct measurement of groundwater-storage change. This report focuses on the southern part of the Big Chino Subbasin for water years 2018–2021. These more recent data show relatively small changes in groundwater storage, consistent with the earlier monitoring presented in U.S. Geological Survey Scientific Investigations Report 2019–5060. In the Big Chino Water Ranch area, water levels have increased gradually owing to discontinued pumping for irrigation during summer months, and an in-channel recharge event in summer 2021. In the Paulden, Arizona, area, gradual water level declines have continued a downward trend that started in the 1990s. Seasonal variation is present in the Paulden area, with higher water levels in the winter months when pumping for irrigation and agricultural use is reduced. Two wells showed groundwater-level increases consistent with in-channel recharge in 2018 and 2021, whereas groundwater levels in a well screened in the deeper, confined to semi-confined carbonate aquifer showed no such discrete recharge events. In the area west of Big Chino Wash and east of the Juniper Mountains and Santa Maria Mountains, groundwater levels continued long-term declines, but storage changes were minimal.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225117","collaboration":"Prepared in Cooperation with the City of Prescott, the Town of Prescott Valley, and Salt River Project","usgsCitation":"Kennedy, J.R., 2022, Aquifer storage change, 2018–2021, in the Big Chino Subbasin, Yavapai County, Arizona: U.S. Geological Survey Scientific Investigations Report 2022–5117, 16 p., https://doi.org/10.3133/sir20225117.","productDescription":"vii, 16 p.","numberOfPages":"16","onlineOnly":"Y","ipdsId":"IP-134054","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":500461,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114443.htm","linkFileType":{"id":5,"text":"html"}},{"id":413723,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5117/images"},{"id":413721,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5117/covrthb.jpg"},{"id":413722,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5117/sir20225117.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigations Report 2022–5117"}],"country":"United States","state":"Arizona","county":"Yavapai County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-111.549,34.4656],[-111.551,34.4656],[-111.551,34.4529],[-111.551,34.4415],[-111.554,34.4393],[-111.563,34.432],[-111.572,34.4293],[-111.574,34.4221],[-111.581,34.4198],[-111.591,34.4208],[-111.592,34.4208],[-111.602,34.4181],[-111.606,34.4149],[-111.605,34.4122],[-111.614,34.4045],[-111.616,34.4036],[-111.627,34.3973],[-111.636,34.3928],[-111.643,34.3928],[-111.649,34.3914],[-111.659,34.3856],[-111.658,34.3783],[-111.658,34.3737],[-111.659,34.3624],[-111.664,34.3556],[-111.667,34.3479],[-111.665,34.3392],[-111.665,34.3315],[-111.664,34.3238],[-111.664,34.3211],[-111.667,34.3129],[-111.669,34.3102],[-111.668,34.3088],[-111.669,34.3074],[-111.67,34.3065],[-111.671,34.3074],[-111.674,34.3074],[-111.675,34.3065],[-111.678,34.3034],[-111.684,34.2998],[-111.685,34.2966],[-111.682,34.2961],[-111.68,34.2938],[-111.68,34.292],[-111.678,34.2893],[-111.675,34.2888],[-111.675,34.2925],[-111.675,34.2943],[-111.673,34.2947],[-111.666,34.2974],[-111.664,34.2947],[-111.665,34.2933],[-111.664,34.2902],[-111.666,34.2852],[-111.671,34.2838],[-111.679,34.2829],[-111.683,34.2829],[-111.685,34.282],[-111.685,34.2807],[-111.683,34.2793],[-111.682,34.2752],[-111.682,34.2729],[-111.68,34.2707],[-111.678,34.2702],[-111.676,34.2693],[-111.678,34.2675],[-111.678,34.2666],[-111.68,34.2657],[-111.682,34.262],[-111.686,34.2602],[-111.689,34.2602],[-111.691,34.2589],[-111.691,34.2557],[-111.692,34.2543],[-111.694,34.2539],[-111.697,34.2503],[-111.698,34.2466],[-111.698,34.2448],[-111.696,34.2448],[-111.694,34.243],[-111.696,34.2416],[-111.697,34.2421],[-111.701,34.2394],[-111.7,34.2362],[-111.7,34.2326],[-111.698,34.2307],[-111.698,34.2294],[-111.701,34.2294],[-111.704,34.2285],[-111.705,34.2253],[-111.703,34.2221],[-111.704,34.2203],[-111.705,34.213],[-111.7,34.2107],[-111.698,34.2112],[-111.696,34.2112],[-111.695,34.2098],[-111.692,34.2062],[-111.69,34.2021],[-111.691,34.1989],[-111.693,34.1971],[-111.694,34.1944],[-111.696,34.193],[-111.7,34.1926],[-111.701,34.1939],[-111.701,34.1962],[-111.702,34.198],[-111.706,34.1989],[-111.711,34.1999],[-111.712,34.1967],[-111.71,34.1939],[-111.706,34.1912],[-111.709,34.1898],[-111.71,34.188],[-111.71,34.1867],[-111.706,34.1871],[-111.703,34.1889],[-111.7,34.1898],[-111.695,34.1884],[-111.694,34.1857],[-111.695,34.1812],[-111.698,34.1803],[-111.699,34.1821],[-111.703,34.183],[-111.706,34.1812],[-111.706,34.1785],[-111.706,34.1758],[-111.709,34.173],[-111.711,34.1703],[-111.714,34.1662],[-111.72,34.1635],[-111.721,34.1613],[-111.72,34.1581],[-111.717,34.1558],[-111.712,34.1512],[-111.664,34.1511],[-111.478,34.1513],[-111.48,34.15],[-111.483,34.1463],[-111.484,34.1418],[-111.488,34.14],[-111.491,34.1377],[-111.493,34.135],[-111.494,34.1328],[-111.492,34.1305],[-111.486,34.1314],[-111.482,34.1318],[-111.48,34.1304],[-111.481,34.1263],[-111.482,34.1227],[-111.481,34.1195],[-111.475,34.1186],[-111.475,34.1163],[-111.474,34.114],[-111.471,34.1122],[-111.473,34.1095],[-111.474,34.1081],[-111.475,34.1054],[-111.479,34.1036],[-111.479,34.1013],[-111.483,34.0991],[-111.485,34.0968],[-111.483,34.0932],[-111.481,34.0886],[-111.479,34.0877],[-111.479,34.0841],[-111.477,34.0827],[-111.477,34.0804],[-111.472,34.079],[-111.471,34.0763],[-111.469,34.0754],[-111.466,34.0726],[-111.465,34.0726],[-111.465,34.0699],[-111.462,34.0676],[-111.461,34.0653],[-111.462,34.0613],[-111.464,34.059],[-111.467,34.059],[-111.468,34.0595],[-111.472,34.0586],[-111.473,34.0563],[-111.472,34.0531],[-111.47,34.0513],[-111.469,34.0486],[-111.469,34.0472],[-111.47,34.0454],[-111.471,34.0458],[-111.472,34.0427],[-111.474,34.0409],[-111.477,34.0409],[-111.48,34.0395],[-111.48,34.0409],[-111.484,34.0404],[-111.485,34.0364],[-111.487,34.0359],[-111.489,34.0364],[-111.494,34.0337],[-111.495,34.0314],[-111.498,34.0296],[-111.495,34.0237],[-111.498,34.0182],[-111.496,34.0169],[-111.496,34.0146],[-111.5,34.011],[-111.5,34.0083],[-111.499,34.0042],[-111.497,34.0037],[-111.496,34],[-111.638,34.0001],[-111.679,34.0002],[-111.709,33.9999],[-111.716,33.9999],[-111.724,34.0004],[-111.807,34.0092],[-112.062,34.037],[-112.114,34.0424],[-112.145,34.0461],[-112.165,34.0474],[-112.163,34.0456],[-112.162,34.0429],[-112.158,34.0438],[-112.154,34.042],[-112.163,34.0374],[-112.165,34.0347],[-112.165,34.0301],[-112.164,34.0256],[-112.162,34.0215],[-112.161,34.0178],[-112.166,34.0128],[-112.168,34.0156],[-112.171,34.0169],[-112.173,34.0183],[-112.176,34.0151],[-112.183,34.0137],[-112.184,34.011],[-112.183,34.0092],[-112.181,34.0069],[-112.18,34.0042],[-112.182,34.0019],[-112.186,33.9978],[-112.189,33.9964],[-112.193,33.9914],[-112.194,33.9873],[-112.194,33.9805],[-112.195,33.9769],[-112.197,33.9732],[-112.201,33.971],[-112.204,33.9701],[-112.209,33.97],[-112.212,33.9687],[-112.216,33.9659],[-112.215,33.9637],[-112.218,33.9618],[-112.222,33.9609],[-112.226,33.9582],[-112.232,33.9545],[-112.234,33.9559],[-112.238,33.9568],[-112.242,33.9559],[-112.239,33.9536],[-112.241,33.9518],[-112.241,33.9486],[-112.238,33.9486],[-112.237,33.9468],[-112.24,33.9427],[-112.242,33.9404],[-112.239,33.9395],[-112.234,33.9373],[-112.233,33.9359],[-112.233,33.9291],[-112.235,33.9177],[-112.237,33.9145],[-112.24,33.9154],[-112.244,33.9159],[-112.241,33.9091],[-112.243,33.9059],[-112.246,33.905],[-112.25,33.9049],[-112.254,33.9058],[-112.258,33.9054],[-112.262,33.9017],[-112.267,33.8967],[-112.271,33.8954],[-112.276,33.8926],[-112.278,33.889],[-112.277,33.8822],[-112.305,33.8898],[-112.364,33.9047],[-112.373,33.9069],[-112.408,33.9154],[-112.459,33.9284],[-112.493,33.9365],[-112.501,33.9382],[-112.513,33.9418],[-112.522,33.944],[-112.53,33.9458],[-112.565,33.9548],[-112.582,33.9592],[-112.689,33.9864],[-112.726,33.9952],[-112.744,33.9997],[-112.769,34],[-112.815,34.0001],[-112.929,34.0024],[-112.946,34.0023],[-112.98,34.0024],[-113.103,34.0023],[-113.156,34.0017],[-113.208,34.0012],[-113.242,34.0013],[-113.334,34.0012],[-113.334,34.0867],[-113.334,34.1166],[-113.334,34.2339],[-113.335,34.3025],[-113.334,34.3175],[-113.333,34.3807],[-113.334,34.4179],[-113.333,34.4334],[-113.333,34.4584],[-113.334,34.5065],[-113.334,34.512],[-113.333,34.5211],[-113.334,34.5365],[-113.333,34.5511],[-113.333,34.5933],[-113.333,34.6092],[-113.334,34.6551],[-113.333,34.656],[-113.333,34.6592],[-113.334,34.6805],[-113.333,34.6955],[-113.334,34.7105],[-113.333,34.7255],[-113.334,34.7405],[-113.333,34.7555],[-113.334,34.7664],[-113.334,34.7964],[-113.334,34.9267],[-113.333,35.1065],[-113.334,35.2609],[-113.334,35.4248],[-113.334,35.5051],[-113.334,35.5278],[-113.329,35.5278],[-113.324,35.5297],[-113.322,35.5302],[-113.316,35.5303],[-113.314,35.5303],[-113.298,35.5304],[-113.296,35.53],[-113.293,35.5291],[-113.289,35.5296],[-113.282,35.5293],[-113.276,35.5298],[-113.275,35.5298],[-113.271,35.5294],[-113.268,35.5299],[-113.266,35.5299],[-113.263,35.5295],[-113.258,35.5273],[-113.254,35.5259],[-113.252,35.525],[-113.243,35.5197],[-113.239,35.5184],[-113.235,35.5166],[-113.232,35.5148],[-113.219,35.5086],[-113.214,35.5091],[-113.207,35.5092],[-113.204,35.5097],[-113.199,35.5106],[-113.196,35.5106],[-113.195,35.5102],[-113.183,35.5076],[-113.178,35.5067],[-113.175,35.5063],[-113.172,35.5054],[-113.169,35.5037],[-113.166,35.5014],[-113.164,35.5001],[-113.163,35.4992],[-113.162,35.4983],[-113.158,35.496],[-113.157,35.4952],[-113.156,35.4938],[-113.155,35.4929],[-113.152,35.4897],[-113.15,35.4861],[-113.15,35.4852],[-113.147,35.4776],[-113.146,35.4776],[-113.144,35.4767],[-113.143,35.4762],[-113.135,35.4727],[-113.131,35.4713],[-113.129,35.4705],[-113.127,35.4691],[-113.123,35.4678],[-113.121,35.4674],[-113.118,35.4656],[-113.117,35.4651],[-113.115,35.4642],[-113.113,35.4638],[-113.111,35.4629],[-113.105,35.4602],[-113.103,35.4598],[-113.102,35.4589],[-113.099,35.4585],[-113.093,35.4549],[-113.086,35.4527],[-113.007,35.4085],[-113.004,35.4071],[-113.003,35.4071],[-113.001,35.4053],[-112.999,35.4049],[-112.997,35.4031],[-112.996,35.4027],[-112.986,35.3982],[-112.973,35.3906],[-112.967,35.3852],[-112.964,35.3811],[-112.963,35.3789],[-112.954,35.3558],[-112.949,35.3545],[-112.945,35.3527],[-112.943,35.3518],[-112.941,35.3518],[-112.933,35.3505],[-112.929,35.3497],[-112.927,35.3497],[-112.915,35.3475],[-112.898,35.3449],[-112.897,35.3445],[-112.89,35.3436],[-112.888,35.3432],[-112.884,35.3427],[-112.881,35.3418],[-112.88,35.3419],[-112.876,35.3405],[-112.868,35.3383],[-112.853,35.3348],[-112.836,35.3313],[-112.826,35.3291],[-112.821,35.3282],[-112.815,35.3269],[-112.811,35.3265],[-112.808,35.326],[-112.797,35.3229],[-112.792,35.3198],[-112.788,35.318],[-112.786,35.3167],[-112.779,35.3149],[-112.777,35.3149],[-112.772,35.3154],[-112.769,35.3149],[-112.763,35.3127],[-112.76,35.3109],[-112.757,35.3087],[-112.755,35.3064],[-112.751,35.306],[-112.748,35.3055],[-112.745,35.3056],[-112.743,35.3051],[-112.741,35.3051],[-112.736,35.3047],[-112.734,35.3052],[-112.727,35.3057],[-112.716,35.3071],[-112.715,35.308],[-112.712,35.3085],[-112.703,35.3113],[-112.7,35.3113],[-112.698,35.3117],[-112.695,35.3118],[-112.689,35.3104],[-112.685,35.3091],[-112.681,35.3087],[-112.676,35.3064],[-112.673,35.3042],[-112.669,35.3019],[-112.666,35.2992],[-112.663,35.2961],[-112.662,35.2934],[-112.659,35.292],[-112.654,35.2938],[-112.651,35.2957],[-112.647,35.2984],[-112.645,35.2994],[-112.641,35.3003],[-112.638,35.3007],[-112.635,35.3003],[-112.628,35.2985],[-112.626,35.2976],[-112.624,35.2967],[-112.622,35.2945],[-112.618,35.2831],[-112.619,35.2804],[-112.62,35.2772],[-112.621,35.275],[-112.62,35.2745],[-112.616,35.2741],[-112.612,35.2727],[-112.604,35.2691],[-112.603,35.2682],[-112.599,35.2646],[-112.598,35.2637],[-112.594,35.2597],[-112.585,35.2511],[-112.585,35.2497],[-112.577,35.243],[-112.569,35.2416],[-112.567,35.2412],[-112.555,35.2385],[-112.54,35.2363],[-112.515,35.2401],[-112.51,35.2405],[-112.506,35.2419],[-112.504,35.2419],[-112.501,35.2424],[-112.498,35.2424],[-112.493,35.242],[-112.484,35.2402],[-112.473,35.2389],[-112.47,35.2434],[-112.468,35.2457],[-112.464,35.2485],[-112.462,35.2498],[-112.46,35.2507],[-112.455,35.2521],[-112.451,35.2544],[-112.449,35.2567],[-112.439,35.2608],[-112.439,35.2535],[-112.439,35.2245],[-112.44,35.1487],[-112.333,35.149],[-112.333,35.0818],[-112.332,35.0773],[-112.331,34.9724],[-112.11,34.9733],[-112.078,34.9738],[-112.019,34.9738],[-112.019,34.9756],[-112.005,34.9756],[-111.84,34.9759],[-111.836,34.9755],[-111.826,34.9755],[-111.811,34.9754],[-111.805,34.9804],[-111.791,34.98],[-111.775,34.9799],[-111.775,34.9713],[-111.775,34.8814],[-111.776,34.8037],[-111.742,34.8028],[-111.644,34.8016],[-111.548,34.8013],[-111.549,34.6891],[-111.549,34.6696],[-111.549,34.5687],[-111.548,34.5456],[-111.549,34.4656]]]},\"properties\":{\"name\":\"Yavapai\",\"state\":\"AZ\"}}]}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Our understanding of the mechanisms that maintain forest diversity under changing climate can benefit from knowledge about traits that are closely linked to fitness. We tested whether the link between traits and seed number and seed size is consistent with two hypotheses, termed the leaf economics spectrum and the plant size syndrome, or whether reproduction represents an independent dimension related to a seed size–seed number trade-off.
Most of the data come from Europe, North and Central America and East Asia. A minority of the data come from South America, Africa and Australia.
1960–2022.
Trees.
We gathered 12 million observations of the number of seeds produced in 784 tree species. We estimated the number of seeds produced by individual trees and scaled it up to the species level. Next, we used principal components analysis and generalized joint attribute modelling (GJAM) to map seed number and size on the tree traits spectrum.
Incorporating seed size and number into trait analysis while controlling for environment and phylogeny with GJAM exposes relationships in trees that might otherwise remain hidden. Production of the large total biomass of seeds [product of seed number and seed size; hereafter, species seed productivity (SSP)] is associated with high leaf area, low foliar nitrogen, low specific leaf area (SLA) and dense wood. Production of high seed numbers is associated with small seeds produced by nutrient-demanding species with softwood, small leaves and high SLA. Trait covariation is consistent with opposing strategies: one fast-growing, early successional, with high dispersal, and the other slow-growing, stress-tolerant, that recruit in shaded conditions.
Earth system models currently assume that reproductive allocation is indifferent among plant functional types. Easily measurable seed size is a strong predictor of the seed number and species seed productivity. The connection of SSP with the functional traits can form the first basis of improved fecundity prediction across global forests.
","language":"English","publisher":"Wiley","doi":"10.1111/geb.13652","usgsCitation":"Bogdziewicz, M., Acuña, M., Andrus, R.A., Ascoli, D., Bergeron, Y., Brveiller, D., Boivin, T., Bonal, R., Caignard, T., Cailleret, M., Calama, R., Calderon, S.D., Camarero, J., Chang-Yang, C., Chave, J., Chianucci, F., Cleavitt, N.L., Courbaud, B., Cutini, A., Curt, T., Das, A., Davi, H., Delpiere, N., Delzon, S., Dietze, M., Dormont, L., Farfan-Rios, W., Gehring, C.A., Gilbert, G.S., Gratzer, G., Greenberg, C.H., Guignabert, A., Guo, Q., Hacket-Pain, A., Hampe, A., Han, Q., Hoshizaki, K., Ibanez, I., Johnstone, J.F., Journe, V., Kitzberger, T., Knops, J., Kunstler, G., Kobe, R., Lageard, J.G., LaMontagne, J., Ledwon, M., Leininger, T., Limousin, J., Lutz, J.A., Macias, D., Marell, A., McIntire, E.J., Moran, E.V., Motta, R., Myers, J.A., Nagel, T.A., Naoe, S., Noguchi, K., Oguro, M., Kurokawa, H., Ourcival, J., Parmenter, R., Perez-Ramos, I., Piechnik, L., Podgorski, T., Poulsen, J., Qiu, T., Redmond, M.D., Reid, C., Rodman, K., Šamonil, P., Holik, J., Scher, C.L., Van Marle, H.S., Seget, B., Shibata, M., Sharma, S., Silman, M., Steele, M.A., Straub, J.N., Sun, I., Sutton, S., Swenson, J., Thomas, P., Uriarte, M., Vacchiano, G., Veblen, T.T., Wright, B., Wright, S.J., Whitham, T.G., Zhu, K., Zimmerman, J.K., Zywiec, M., and Clark, J.S., 2023, Linking seed size and number to trait syndromes in trees: Global Ecology and Biogeography, v. 32, no. 5, p. 683-694, https://doi.org/10.1111/geb.13652.","productDescription":"12 p.","startPage":"683","endPage":"694","ipdsId":"IP-149887","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":444282,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.inrae.fr/hal-04032674","text":"External Repository"},{"id":414212,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Bogdziewicz, Michal","contributorId":256849,"corporation":false,"usgs":false,"family":"Bogdziewicz","given":"Michal","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":866434,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Acuña, Marie-Claire Aravena","contributorId":303057,"corporation":false,"usgs":false,"family":"Acuña","given":"Marie-Claire Aravena","affiliations":[{"id":65630,"text":"Laboratorio de Recursos Agroforestales, Centro Austral de Investigaciones Científicas, Argentina.","active":true,"usgs":false}],"preferred":false,"id":866435,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andrus, Robert A.","contributorId":229021,"corporation":false,"usgs":false,"family":"Andrus","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":41541,"text":"Department of Geography, University of Colorado Boulder, Guggenheim 110, 260 UCB, Boulder, Colorado, 80309-0260, USA","active":true,"usgs":false}],"preferred":false,"id":866436,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ascoli, Davide","contributorId":224289,"corporation":false,"usgs":false,"family":"Ascoli","given":"Davide","email":"","affiliations":[{"id":40848,"text":"University of Torino","active":true,"usgs":false}],"preferred":false,"id":866437,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bergeron, Yves","contributorId":256848,"corporation":false,"usgs":false,"family":"Bergeron","given":"Yves","email":"","affiliations":[{"id":40150,"text":"Adam Mickiewicz University, Poland","active":true,"usgs":false}],"preferred":false,"id":866438,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brveiller, Daniel","contributorId":303058,"corporation":false,"usgs":false,"family":"Brveiller","given":"Daniel","email":"","affiliations":[{"id":65631,"text":"CNRS, Université Paris-Saclay, AgroParisTech, France","active":true,"usgs":false}],"preferred":false,"id":866439,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boivin, Thomas","contributorId":268820,"corporation":false,"usgs":false,"family":"Boivin","given":"Thomas","email":"","affiliations":[{"id":55680,"text":"INRAE, France","active":true,"usgs":false}],"preferred":false,"id":866440,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bonal, Raul","contributorId":268821,"corporation":false,"usgs":false,"family":"Bonal","given":"Raul","email":"","affiliations":[{"id":55681,"text":"University of Madrid","active":true,"usgs":false}],"preferred":false,"id":866441,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Caignard, Thomas","contributorId":268822,"corporation":false,"usgs":false,"family":"Caignard","given":"Thomas","email":"","affiliations":[{"id":55680,"text":"INRAE, France","active":true,"usgs":false}],"preferred":false,"id":866442,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cailleret, Maxime 0000-0001-6561-1943","orcid":"https://orcid.org/0000-0001-6561-1943","contributorId":181952,"corporation":false,"usgs":false,"family":"Cailleret","given":"Maxime","email":"","affiliations":[],"preferred":false,"id":866443,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Calama, Rafael","contributorId":268823,"corporation":false,"usgs":false,"family":"Calama","given":"Rafael","email":"","affiliations":[{"id":55682,"text":"INIA-CIFOR, Spain","active":true,"usgs":false}],"preferred":false,"id":866444,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Calderon, Sergio Donoso","contributorId":303059,"corporation":false,"usgs":false,"family":"Calderon","given":"Sergio","email":"","middleInitial":"Donoso","affiliations":[{"id":65632,"text":"Universidad de Chile, Chile","active":true,"usgs":false}],"preferred":false,"id":866445,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Camarero, J. Julio","contributorId":303060,"corporation":false,"usgs":false,"family":"Camarero","given":"J. Julio","affiliations":[{"id":65633,"text":"Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC), Spain","active":true,"usgs":false}],"preferred":false,"id":866446,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Chang-Yang, Chia-Hao","contributorId":303061,"corporation":false,"usgs":false,"family":"Chang-Yang","given":"Chia-Hao","email":"","affiliations":[{"id":65634,"text":"National Sun Yat-sen University, Kaohsiung, Taiwan","active":true,"usgs":false}],"preferred":false,"id":866447,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Chave, Jerome","contributorId":303062,"corporation":false,"usgs":false,"family":"Chave","given":"Jerome","email":"","affiliations":[{"id":65635,"text":"Laboratoire Évolution et Diversité Biologique, UMR 5174 (CNRS/IRD/UPS), CNRS, Toulouse, France","active":true,"usgs":false}],"preferred":false,"id":866448,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Chianucci, Francesco","contributorId":302444,"corporation":false,"usgs":false,"family":"Chianucci","given":"Francesco","email":"","affiliations":[],"preferred":false,"id":866449,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Cleavitt, Natalie L.","contributorId":303063,"corporation":false,"usgs":false,"family":"Cleavitt","given":"Natalie","email":"","middleInitial":"L.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":866450,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Courbaud, Benoit","contributorId":256858,"corporation":false,"usgs":false,"family":"Courbaud","given":"Benoit","email":"","affiliations":[{"id":39773,"text":"Univ. Grenoble Alpes, France","active":true,"usgs":false}],"preferred":false,"id":866451,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Cutini, Andrea","contributorId":302447,"corporation":false,"usgs":false,"family":"Cutini","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":866452,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Curt, Thomas","contributorId":303064,"corporation":false,"usgs":false,"family":"Curt","given":"Thomas","email":"","affiliations":[{"id":65637,"text":"Aix Marseille universite, Institut National de Recherche pour Agriculture, Alimentation et Environnement (IN- RAE), Aix-en-Provence, France","active":true,"usgs":false}],"preferred":false,"id":866453,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Das, Adrian 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":201236,"corporation":false,"usgs":true,"family":"Das","given":"Adrian","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":866454,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Davi, Hendrik","contributorId":181968,"corporation":false,"usgs":false,"family":"Davi","given":"Hendrik","email":"","affiliations":[],"preferred":false,"id":866455,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Delpiere, Nicolas","contributorId":303065,"corporation":false,"usgs":false,"family":"Delpiere","given":"Nicolas","email":"","affiliations":[{"id":65639,"text":"Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Systématique et Evolution, 91190, Gif-sur-Yvette, France","active":true,"usgs":false}],"preferred":false,"id":866456,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Delzon, Sylvain","contributorId":181969,"corporation":false,"usgs":false,"family":"Delzon","given":"Sylvain","email":"","affiliations":[],"preferred":false,"id":866457,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Dietze, Michael","contributorId":248349,"corporation":false,"usgs":false,"family":"Dietze","given":"Michael","affiliations":[],"preferred":false,"id":866458,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Dormont, Laurent","contributorId":303066,"corporation":false,"usgs":false,"family":"Dormont","given":"Laurent","email":"","affiliations":[{"id":65640,"text":"Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Centre National de la Recherche Scientifique (CNRS), Montpellier, France","active":true,"usgs":false}],"preferred":false,"id":866459,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Farfan-Rios, William","contributorId":268827,"corporation":false,"usgs":false,"family":"Farfan-Rios","given":"William","email":"","affiliations":[{"id":37383,"text":"Washington University","active":true,"usgs":false}],"preferred":false,"id":866460,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Gehring, Catherine A.","contributorId":189076,"corporation":false,"usgs":false,"family":"Gehring","given":"Catherine","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":866461,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Gilbert, Gregory S.","contributorId":220542,"corporation":false,"usgs":false,"family":"Gilbert","given":"Gregory","email":"","middleInitial":"S.","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":866462,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Gratzer, Georg","contributorId":302453,"corporation":false,"usgs":false,"family":"Gratzer","given":"Georg","email":"","affiliations":[],"preferred":false,"id":866463,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Greenberg, Cathryn H.","contributorId":268828,"corporation":false,"usgs":false,"family":"Greenberg","given":"Cathryn","email":"","middleInitial":"H.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":866464,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Guignabert, Arthur","contributorId":303067,"corporation":false,"usgs":false,"family":"Guignabert","given":"Arthur","email":"","affiliations":[{"id":65641,"text":"INRAE, Bordeaux Sciences Agro, UMR 1391 ISPA, Villenave d’Ornon, France","active":true,"usgs":false}],"preferred":false,"id":866465,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Guo, Qinfeng","contributorId":214263,"corporation":false,"usgs":false,"family":"Guo","given":"Qinfeng","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":866466,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Hacket-Pain, Andrew","contributorId":224290,"corporation":false,"usgs":false,"family":"Hacket-Pain","given":"Andrew","affiliations":[{"id":16977,"text":"University of Liverpool","active":true,"usgs":false}],"preferred":false,"id":866467,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Hampe, Arndt","contributorId":303068,"corporation":false,"usgs":false,"family":"Hampe","given":"Arndt","email":"","affiliations":[{"id":65642,"text":"INRAE, Biodiversity, Genes, and Communities (BIOGECO), Pessac, France","active":true,"usgs":false}],"preferred":false,"id":866468,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Han, Qingmin","contributorId":303069,"corporation":false,"usgs":false,"family":"Han","given":"Qingmin","email":"","affiliations":[{"id":65643,"text":"Forestry and Forest Products Research Institute (FFPRI), Tsukuba, Ibaraki, Japan","active":true,"usgs":false}],"preferred":false,"id":866469,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Hoshizaki, Kazuhiko","contributorId":303070,"corporation":false,"usgs":false,"family":"Hoshizaki","given":"Kazuhiko","email":"","affiliations":[{"id":65644,"text":"Akita Prefectural University, Akita, Japan","active":true,"usgs":false}],"preferred":false,"id":866470,"contributorType":{"id":1,"text":"Authors"},"rank":37},{"text":"Ibanez, Ines","contributorId":236833,"corporation":false,"usgs":false,"family":"Ibanez","given":"Ines","affiliations":[],"preferred":false,"id":866471,"contributorType":{"id":1,"text":"Authors"},"rank":38},{"text":"Johnstone, Jill F.","contributorId":179336,"corporation":false,"usgs":false,"family":"Johnstone","given":"Jill","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":866472,"contributorType":{"id":1,"text":"Authors"},"rank":39},{"text":"Journe, Valentin","contributorId":303071,"corporation":false,"usgs":false,"family":"Journe","given":"Valentin","email":"","affiliations":[{"id":65645,"text":"Universite Grenoble Alpes, France","active":true,"usgs":false}],"preferred":false,"id":866473,"contributorType":{"id":1,"text":"Authors"},"rank":40},{"text":"Kitzberger, Thomas","contributorId":181980,"corporation":false,"usgs":false,"family":"Kitzberger","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":866474,"contributorType":{"id":1,"text":"Authors"},"rank":41},{"text":"Knops, Johannes M.H.","contributorId":293505,"corporation":false,"usgs":false,"family":"Knops","given":"Johannes M.H.","affiliations":[{"id":63320,"text":"Xi’an Jiaotong Liverpool University","active":true,"usgs":false}],"preferred":false,"id":866475,"contributorType":{"id":1,"text":"Authors"},"rank":42},{"text":"Kunstler, Georges","contributorId":198539,"corporation":false,"usgs":false,"family":"Kunstler","given":"Georges","email":"","affiliations":[],"preferred":false,"id":866476,"contributorType":{"id":1,"text":"Authors"},"rank":43},{"text":"Kobe, Richard","contributorId":268832,"corporation":false,"usgs":false,"family":"Kobe","given":"Richard","affiliations":[{"id":41642,"text":"Michigan State U","active":true,"usgs":false}],"preferred":false,"id":866477,"contributorType":{"id":1,"text":"Authors"},"rank":44},{"text":"Lageard, Jonathan G. A.","contributorId":303072,"corporation":false,"usgs":false,"family":"Lageard","given":"Jonathan","email":"","middleInitial":"G. A.","affiliations":[{"id":65646,"text":"Manchester Metropolitan University, Manchester, UK","active":true,"usgs":false}],"preferred":false,"id":866478,"contributorType":{"id":1,"text":"Authors"},"rank":45},{"text":"LaMontagne, Jalene M.","contributorId":224291,"corporation":false,"usgs":false,"family":"LaMontagne","given":"Jalene M.","affiliations":[{"id":36623,"text":"DePaul University","active":true,"usgs":false}],"preferred":false,"id":866479,"contributorType":{"id":1,"text":"Authors"},"rank":46},{"text":"Ledwon, Mateusz","contributorId":268834,"corporation":false,"usgs":false,"family":"Ledwon","given":"Mateusz","email":"","affiliations":[{"id":55688,"text":"Polish Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":866480,"contributorType":{"id":1,"text":"Authors"},"rank":47},{"text":"Leininger, Theodor","contributorId":303073,"corporation":false,"usgs":false,"family":"Leininger","given":"Theodor","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":866481,"contributorType":{"id":1,"text":"Authors"},"rank":48},{"text":"Limousin, Jean-Marc","contributorId":199453,"corporation":false,"usgs":false,"family":"Limousin","given":"Jean-Marc","email":"","affiliations":[],"preferred":false,"id":866482,"contributorType":{"id":1,"text":"Authors"},"rank":49},{"text":"Lutz, James A.","contributorId":139178,"corporation":false,"usgs":false,"family":"Lutz","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":12682,"text":"Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":866483,"contributorType":{"id":1,"text":"Authors"},"rank":50},{"text":"Macias, Diana","contributorId":256880,"corporation":false,"usgs":false,"family":"Macias","given":"Diana","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":866484,"contributorType":{"id":1,"text":"Authors"},"rank":51},{"text":"Marell, Anders","contributorId":303074,"corporation":false,"usgs":false,"family":"Marell","given":"Anders","affiliations":[{"id":65647,"text":"INRAE, UR EFNO, F-45290 Nogent-sur-Vernisson, France","active":true,"usgs":false}],"preferred":false,"id":866485,"contributorType":{"id":1,"text":"Authors"},"rank":52},{"text":"McIntire, Eliot J.B.","contributorId":303075,"corporation":false,"usgs":false,"family":"McIntire","given":"Eliot","email":"","middleInitial":"J.B.","affiliations":[{"id":65648,"text":"Pacific Forestry Centre, Victoria, British Columbia, Canada","active":true,"usgs":false}],"preferred":false,"id":866486,"contributorType":{"id":1,"text":"Authors"},"rank":53},{"text":"Moran, Emily V.","contributorId":216568,"corporation":false,"usgs":false,"family":"Moran","given":"Emily","email":"","middleInitial":"V.","affiliations":[{"id":16805,"text":"University of California, Merced","active":true,"usgs":false}],"preferred":false,"id":866487,"contributorType":{"id":1,"text":"Authors"},"rank":54},{"text":"Motta, Renzo","contributorId":224294,"corporation":false,"usgs":false,"family":"Motta","given":"Renzo","email":"","affiliations":[{"id":40848,"text":"University of Torino","active":true,"usgs":false}],"preferred":false,"id":866488,"contributorType":{"id":1,"text":"Authors"},"rank":55},{"text":"Myers, Jonathan A.","contributorId":197852,"corporation":false,"usgs":false,"family":"Myers","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":866489,"contributorType":{"id":1,"text":"Authors"},"rank":56},{"text":"Nagel, Thomas A.","contributorId":268835,"corporation":false,"usgs":false,"family":"Nagel","given":"Thomas","email":"","middleInitial":"A.","affiliations":[{"id":40950,"text":"University of Ljubljana","active":true,"usgs":false}],"preferred":false,"id":866490,"contributorType":{"id":1,"text":"Authors"},"rank":57},{"text":"Naoe, Shoji","contributorId":303076,"corporation":false,"usgs":false,"family":"Naoe","given":"Shoji","email":"","affiliations":[{"id":65649,"text":"Tohoku Research Center, Forestry and Forest Products Research Institute, Tsukuba, Ibaraki, Japan","active":true,"usgs":false}],"preferred":false,"id":866491,"contributorType":{"id":1,"text":"Authors"},"rank":58},{"text":"Noguchi, Kyotaro","contributorId":268836,"corporation":false,"usgs":false,"family":"Noguchi","given":"Kyotaro","email":"","affiliations":[{"id":55689,"text":"Forestry and Forest Products Research Institute, Japan","active":true,"usgs":false}],"preferred":false,"id":866492,"contributorType":{"id":1,"text":"Authors"},"rank":59},{"text":"Oguro, Michio","contributorId":303077,"corporation":false,"usgs":false,"family":"Oguro","given":"Michio","email":"","affiliations":[{"id":65650,"text":"Tohoku Research Center, Forestry and Forest Products Research Institute, Tsukuba, Ibaraki, 305-8687, Japan","active":true,"usgs":false}],"preferred":false,"id":866493,"contributorType":{"id":1,"text":"Authors"},"rank":60},{"text":"Kurokawa, Hiroko","contributorId":303078,"corporation":false,"usgs":false,"family":"Kurokawa","given":"Hiroko","email":"","affiliations":[{"id":65650,"text":"Tohoku Research Center, Forestry and Forest Products Research Institute, Tsukuba, Ibaraki, 305-8687, Japan","active":true,"usgs":false}],"preferred":false,"id":866494,"contributorType":{"id":1,"text":"Authors"},"rank":61},{"text":"Ourcival, Jean-Marc","contributorId":303079,"corporation":false,"usgs":false,"family":"Ourcival","given":"Jean-Marc","email":"","affiliations":[{"id":65651,"text":"CEFE, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France","active":true,"usgs":false}],"preferred":false,"id":866495,"contributorType":{"id":1,"text":"Authors"},"rank":62},{"text":"Parmenter, Robert","contributorId":243994,"corporation":false,"usgs":false,"family":"Parmenter","given":"Robert","affiliations":[{"id":48788,"text":"Valles Caldera National Preserve, U.S. National Park Service","active":true,"usgs":false}],"preferred":false,"id":866496,"contributorType":{"id":1,"text":"Authors"},"rank":63},{"text":"Perez-Ramos, Ignacio M.","contributorId":303080,"corporation":false,"usgs":false,"family":"Perez-Ramos","given":"Ignacio M.","affiliations":[{"id":65652,"text":"Inst. de Recursos Naturales y Agrobiologia de Sevilla, Consejo Superior de Investigaciones Cientificas (IRNAS-CSIC), Seville, Andalucia, Spain","active":true,"usgs":false}],"preferred":false,"id":866497,"contributorType":{"id":1,"text":"Authors"},"rank":64},{"text":"Piechnik, Lukasz","contributorId":268838,"corporation":false,"usgs":false,"family":"Piechnik","given":"Lukasz","affiliations":[{"id":55688,"text":"Polish Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":866498,"contributorType":{"id":1,"text":"Authors"},"rank":65},{"text":"Podgorski, Tomasz","contributorId":303081,"corporation":false,"usgs":false,"family":"Podgorski","given":"Tomasz","email":"","affiliations":[{"id":65653,"text":"Czech University of Life Sciences Prague, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":866499,"contributorType":{"id":1,"text":"Authors"},"rank":66},{"text":"Poulsen, John","contributorId":303082,"corporation":false,"usgs":false,"family":"Poulsen","given":"John","email":"","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":866500,"contributorType":{"id":1,"text":"Authors"},"rank":67},{"text":"Qiu, Tong","contributorId":268817,"corporation":false,"usgs":false,"family":"Qiu","given":"Tong","affiliations":[{"id":55678,"text":"Duke U","active":true,"usgs":false}],"preferred":false,"id":866501,"contributorType":{"id":1,"text":"Authors"},"rank":68},{"text":"Redmond, Miranda D.","contributorId":303083,"corporation":false,"usgs":false,"family":"Redmond","given":"Miranda","email":"","middleInitial":"D.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":866502,"contributorType":{"id":1,"text":"Authors"},"rank":69},{"text":"Reid, Chantal D.","contributorId":268841,"corporation":false,"usgs":false,"family":"Reid","given":"Chantal D.","affiliations":[{"id":55678,"text":"Duke U","active":true,"usgs":false}],"preferred":false,"id":866503,"contributorType":{"id":1,"text":"Authors"},"rank":70},{"text":"Rodman, Kyle C.","contributorId":238090,"corporation":false,"usgs":false,"family":"Rodman","given":"Kyle C.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":866504,"contributorType":{"id":1,"text":"Authors"},"rank":71},{"text":"Šamonil, Pavel","contributorId":289225,"corporation":false,"usgs":false,"family":"Šamonil","given":"Pavel","affiliations":[{"id":62072,"text":"The Silva Tarouca Research Institute for Landscape and Ornamental Gardening","active":true,"usgs":false}],"preferred":false,"id":866505,"contributorType":{"id":1,"text":"Authors"},"rank":72},{"text":"Holik, Jan","contributorId":303084,"corporation":false,"usgs":false,"family":"Holik","given":"Jan","affiliations":[{"id":65654,"text":"Silva Tarouca Research Institute, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":866506,"contributorType":{"id":1,"text":"Authors"},"rank":73},{"text":"Scher, C. Lane","contributorId":268843,"corporation":false,"usgs":false,"family":"Scher","given":"C.","email":"","middleInitial":"Lane","affiliations":[{"id":40036,"text":"Duke U.","active":true,"usgs":false}],"preferred":false,"id":866507,"contributorType":{"id":1,"text":"Authors"},"rank":74},{"text":"Van Marle, Harald Schmidt","contributorId":303085,"corporation":false,"usgs":false,"family":"Van Marle","given":"Harald","email":"","middleInitial":"Schmidt","affiliations":[{"id":49135,"text":"Universidad de Chile, Santiago, Chile","active":true,"usgs":false}],"preferred":false,"id":866508,"contributorType":{"id":1,"text":"Authors"},"rank":75},{"text":"Seget, Barbara","contributorId":268845,"corporation":false,"usgs":false,"family":"Seget","given":"Barbara","email":"","affiliations":[{"id":55688,"text":"Polish Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":866509,"contributorType":{"id":1,"text":"Authors"},"rank":76},{"text":"Shibata, Mitsue","contributorId":303086,"corporation":false,"usgs":false,"family":"Shibata","given":"Mitsue","affiliations":[{"id":65650,"text":"Tohoku Research Center, Forestry and Forest Products Research Institute, Tsukuba, Ibaraki, 305-8687, Japan","active":true,"usgs":false}],"preferred":false,"id":866510,"contributorType":{"id":1,"text":"Authors"},"rank":77},{"text":"Sharma, Shubhi","contributorId":256893,"corporation":false,"usgs":false,"family":"Sharma","given":"Shubhi","email":"","affiliations":[{"id":51889,"text":"Department of Geography, University of Colorado Boulder, Boulder, CO 80309","active":true,"usgs":false}],"preferred":false,"id":866511,"contributorType":{"id":1,"text":"Authors"},"rank":78},{"text":"Silman, Miles","contributorId":268846,"corporation":false,"usgs":false,"family":"Silman","given":"Miles","email":"","affiliations":[{"id":36744,"text":"Wake Forest University","active":true,"usgs":false}],"preferred":false,"id":866512,"contributorType":{"id":1,"text":"Authors"},"rank":79},{"text":"Steele, Michael A.","contributorId":256894,"corporation":false,"usgs":false,"family":"Steele","given":"Michael","email":"","middleInitial":"A.","affiliations":[{"id":51892,"text":"Department of Biology, Wilkes University, 84 West South Street, Wilkes-Barre, PA 18766","active":true,"usgs":false}],"preferred":false,"id":866513,"contributorType":{"id":1,"text":"Authors"},"rank":80},{"text":"Straub, Jacob N.","contributorId":130962,"corporation":false,"usgs":false,"family":"Straub","given":"Jacob","email":"","middleInitial":"N.","affiliations":[{"id":7179,"text":"Ctr for Earth & Envir Sc, St Univ of NY-Plattsburgh, NY","active":true,"usgs":false}],"preferred":false,"id":866514,"contributorType":{"id":1,"text":"Authors"},"rank":81},{"text":"Sun, I-Fang","contributorId":197843,"corporation":false,"usgs":false,"family":"Sun","given":"I-Fang","email":"","affiliations":[],"preferred":false,"id":866515,"contributorType":{"id":1,"text":"Authors"},"rank":82},{"text":"Sutton, Samantha","contributorId":256895,"corporation":false,"usgs":false,"family":"Sutton","given":"Samantha","email":"","affiliations":[{"id":51889,"text":"Department of Geography, University of Colorado Boulder, Boulder, CO 80309","active":true,"usgs":false}],"preferred":false,"id":866516,"contributorType":{"id":1,"text":"Authors"},"rank":83},{"text":"Swenson, Jennifer J.","contributorId":268847,"corporation":false,"usgs":false,"family":"Swenson","given":"Jennifer J.","affiliations":[{"id":55678,"text":"Duke U","active":true,"usgs":false}],"preferred":false,"id":866517,"contributorType":{"id":1,"text":"Authors"},"rank":84},{"text":"Thomas, Peter A.","contributorId":302432,"corporation":false,"usgs":false,"family":"Thomas","given":"Peter A.","affiliations":[],"preferred":false,"id":866518,"contributorType":{"id":1,"text":"Authors"},"rank":85},{"text":"Uriarte, Maria","contributorId":287019,"corporation":false,"usgs":false,"family":"Uriarte","given":"Maria","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":866519,"contributorType":{"id":1,"text":"Authors"},"rank":86},{"text":"Vacchiano, Giorgio","contributorId":224295,"corporation":false,"usgs":false,"family":"Vacchiano","given":"Giorgio","email":"","affiliations":[{"id":40851,"text":"University of Milan","active":true,"usgs":false}],"preferred":false,"id":866520,"contributorType":{"id":1,"text":"Authors"},"rank":87},{"text":"Veblen, Thomas T.","contributorId":218196,"corporation":false,"usgs":false,"family":"Veblen","given":"Thomas","email":"","middleInitial":"T.","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":866521,"contributorType":{"id":1,"text":"Authors"},"rank":88},{"text":"Wright, Boyd","contributorId":303087,"corporation":false,"usgs":false,"family":"Wright","given":"Boyd","email":"","affiliations":[{"id":65655,"text":"University of New England, Armidale, New South Wales, Australia","active":true,"usgs":false}],"preferred":false,"id":866522,"contributorType":{"id":1,"text":"Authors"},"rank":89},{"text":"Wright, S. Joseph","contributorId":303088,"corporation":false,"usgs":false,"family":"Wright","given":"S.","email":"","middleInitial":"Joseph","affiliations":[{"id":65656,"text":"Smithsonian Tropical Research Institute, Republic of Panama","active":true,"usgs":false}],"preferred":false,"id":866523,"contributorType":{"id":1,"text":"Authors"},"rank":90},{"text":"Whitham, Thomas G.","contributorId":174327,"corporation":false,"usgs":false,"family":"Whitham","given":"Thomas","email":"","middleInitial":"G.","affiliations":[{"id":27416,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Nothern Arizona University, Flagstaff, AZ 86011 USA","active":true,"usgs":false}],"preferred":false,"id":866524,"contributorType":{"id":1,"text":"Authors"},"rank":91},{"text":"Zhu, Kai","contributorId":256900,"corporation":false,"usgs":false,"family":"Zhu","given":"Kai","email":"","affiliations":[{"id":51894,"text":"University California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":866525,"contributorType":{"id":1,"text":"Authors"},"rank":92},{"text":"Zimmerman, Jess K.","contributorId":196419,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Jess","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":866526,"contributorType":{"id":1,"text":"Authors"},"rank":93},{"text":"Zywiec, Magdalna","contributorId":303089,"corporation":false,"usgs":false,"family":"Zywiec","given":"Magdalna","affiliations":[{"id":65657,"text":"W. Szafer Institute of Botany, Polish Academy of Sciences, Krakow, Poland","active":true,"usgs":false}],"preferred":false,"id":866527,"contributorType":{"id":1,"text":"Authors"},"rank":94},{"text":"Clark, James S.","contributorId":248348,"corporation":false,"usgs":false,"family":"Clark","given":"James","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":866528,"contributorType":{"id":1,"text":"Authors"},"rank":95}]}} ,{"id":70241001,"text":"ofr20231013 - 2023 - ECCOE Landsat quarterly Calibration and Validation report—Quarter 3, 2022","interactions":[],"lastModifiedDate":"2023-03-06T19:07:27.113555","indexId":"ofr20231013","displayToPublicDate":"2023-03-06T13:07:01","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1013","displayTitle":"ECCOE Landsat Quarterly Calibration and Validation Report—Quarter 3, 2022","title":"ECCOE Landsat quarterly Calibration and Validation report—Quarter 3, 2022","docAbstract":"The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level.
This report provides observed geometric and radiometric analysis results for Landsats 7–8 for quarter 3 (July–September) of 2022. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov.
One specific activity that the ECCOE Landsat Cal/Val Team closely monitored was the lowering of the Landsat 7 orbit. On April 6, 2022, the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor was placed into standby mode, and a series of spacecraft burns was completed through the month of April to lower the satellite’s orbit by 8 kilometers. Imaging resumed at a lower orbit of 697 kilometers on May 5, 2022, extending the science mission to allow for essential data acquisition during the 2022 Northern Hemisphere fire and growing season. Additional information about the Landsat 7 orbit lowering is here: https://www.usgs.gov/centers/eros/news/landsat-7-lowered-standard-landsat-orbit#:~:text=The%20satellite's%20primary%20science%20mission%20has%20ended&text=On%20April%206%2C%202022%2C%20the,satellite's%20orbit%20by%208%20kilometers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231013","usgsCitation":"Haque, M.O., Rengarajan, R., Lubke, M., Hasan, M.N., Shrestha, A., Tuli, F.T., Shaw, J.L., Denevan, A., Franks, S.,\nMicijevic, E., Choate, M.J., Anderson, C., Thome, K., Kaita, E., Barsi, J., Levy, R., and Miller, J., 2023, ECCOE Landsat\nquarterly Calibration and Validation report—Quarter 3, 2022: U.S. Geological Survey Open-File Report 2023–1013, 38 p., https://doi.org/10.3133/ofr20231013.","productDescription":"Report: vii, 38 p.; Dataset","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-146519","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":413661,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1013/images"},{"id":413659,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1013/coverthb.jpg"},{"id":413663,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1013/ofr20231013.XML","text":"Report","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2022-1013"},{"id":413662,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov","text":"USGS database","linkHelpText":"—EarthExplorer"},{"id":413660,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1013/ofr20231013.pdf","text":"Report","size":"3.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1013"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The WaterML2: Part 3 - Surface Hydrology Features (HY_Features) Conceptual Model was published by OGC in 2018. This report documents the use of HY_Features concepts in support of two key tasks: (1) local to continental hydrologic modeling; and (2) referencing river corridor data to hydrographic networks. The presented use cases are applicable in hydroscience research and assessments, water resources engineering practices, and drought and flood responses.
Before the HY_Features conceptual model there was no internationally recognized standard for the design of software and data for the hydroscience and engineering community. This report presents progress towards a logical data model that interprets the abstract HY_Features concepts for use in geospatial workflows, modeling applications, and web data systems that integrate hydrologic data.
The use cases addressed include: (1) hydrologic model control volume definition; (2) hydrologic network connectivity; (3) characterization of catchments with landscape and atmospheric data; (4) river corridor characterization; (5) hydrologic location; and (6) flow network location. Each use case is described briefly along with an analysis of the information requirements. This report presents a summary of the logical model designed to satisfy the needs of these use cases and a summary of updates and changes proposed for HY_Features.
Changes for consideration by the HY_Features Standards Working Group include the following.
Provide more clarity on the inherited properties and associations of features that \"realize\" the catchment and nexus concepts from HY_Features.
Add nexus realization feature types to represent the outlet of catchments that are \"frontal\" (terminate to the ocean or a large waterbody) or \"inland sinks.\"
Add a \"HY_Flowline\" feature as a superclass of HY_Flowpath providing linear referencing on waterbodies that are not catchment realizations.
Add an association or interface to support connection between surface catchments and hydrogeologic units.
In large lake systems the nearshore habitat is an intermediate zone between the shoreline and offshore, is an important nursery for larval fish, and is highlighted as an area in need of research in the Laurentian Great Lakes. In this study, we used two long-term monitoring programs to characterize the nearshore zooplankton community composition using seasonal data (May – October) and to compare the nearshore and offshore zooplankton community composition changes over time (1998 – 2019) to determine if the changes were synchronized. In the nearshore, we found the highest zooplankton biomass during the late summer/early fall (August 27th – Oct 6th), compared to mid-summer (July 1st – Aug 26th) and late spring (May 20th – June 30th). In the summer, the nearshore zooplankton community was dominated by cladocerans while copepods dominated the offshore community. From 1998 to 2019, both nearshore and offshore copepods shifted from a cyclopoid to a calanoid-dominated state, but the details of this change were different. For example, taxon-specific analysis revealed that despite reduced cyclopoids in both habitats, Mesocyclops edax increased in the nearshore. Additionally, taxon-specific analysis suggested the changes occurred an average of three years earlier in the nearshore. Using Analysis of Similarity, the nearshore and offshore summer zooplankton community compositions became increasingly distinct over time. Results from this study highlight the uniqueness of the nearshore in large lake systems, the importance of seasonal and long-term monitoring, and the potential of the nearshore as an early indicator of offshore changes.
In underground environments, conventional direct current (DC) resistivity surveys with a single linear array of electrodes produce fundamentally non-unique inversions. These non-uniqueness and model resolution issues stem from limitations placed on the location of transmitters (TXs) and receivers (RXs) by the geometry of existing tunnels and boreholes. Poor excitation and/or sampling of the region of interest (ROI) can create artifacts and reduce the resolution of the recovered model.
To address these problems we propose the use of an ensemble of ring arrays, which are created by placing one or more electrodes in each face (sidewalls, floor, and ceiling) of the tunnel to form a ring of electrodes at each along-tunnel location. Using a series of increasingly complex synthetic models, we assess the benefits of ring arrays and show that they can be used to better constrain the location and shape of anomalous bodies around the tunnel.
Although ring arrays significantly improve the resolution of the recovered model, the size of the comprehensive ring array survey increases rapidly with the number of electrodes used. To balance model resolution and survey size, we developed a physics-based survey design methodology. In this methodology, TXs are selected based upon secondary charge accumulations on a test block that is moved throughout the ROI. Although this survey design methodology does not produce a strictly optimal survey, it balances model resolution and survey size in a practical and computationally efficient manner.
Since the ring array more accurately estimates the around-tunnel location of targets and ensures that targets on all sides of the tunnel are detected, it is ideally suited to tunnel-based environments. Our results show that only about
Ecological condition continues to decline in arid and semi-arid river basins globally due to hydrological over-abstraction combined with changing climatic conditions. Whilst provision of water for the environment has been a primary approach to alleviate ecological decline, how to accurately monitor changes in riverine trees at fine spatial and temporal scales, remains a substantial challenge. This is further complicated by constantly changing water availability across expansive river basins with varying climatic zones. Within, we combine rare, fine-scale, high frequency temporal in-situ field collected data with machine learning and remote sensing, to provide a robust model that enables broadscale monitoring of physiological tree water stress response to environmental changes via actual evapotranspiration (ET). Physiological variation of Eucalyptus camaldulensis (River Red Gum) and E. largiflorens (Black Box) trees across 10 study locations in the southern Murray-Darling Basin, Australia, was captured instantaneously using sap flow sensors, substantially reducing tree response lags encountered by monitoring visual canopy changes. Actual ET measurement of both species was used to bias correct a national spatial ET product where a Random Forest model was trained using continuous timeseries of in-situ data of up to four years. Precise monthly AMLETT (Australia-wide Machine Learning ET for Trees) ET outputs in 30 m pixel resolution from 2012 to 2021, were derived by incorporating additional remote sensing layers such as soil moisture, land surface temperature, radiation and EVI and NDVI in the Random Forest model. Landsat and Sentinal-2 correlation results between in-situ ET and AMLETT ET returned R2 of 0.94 (RMSE 6.63 mm period−1) and 0.92 (RMSE 6.89 mm period−1), respectively. In comparison, correlation between in-situ ET and a national ET product returned R2 of 0.44 (RMSE 34.08 mm period−1) highlighting the need for bias correction to generate accurate absolute ET values. The AMLETT method presented here, enhances environmental management in river basins worldwide. Such robust broadscale monitoring can inform water accounting and importantly, assist decisions on where to prioritize water for the environment to restore and protect key ecological assets and preserve floodplain and riparian ecological function.