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Swedberg K, Cardoso DS, Castillo-Castillo A, Mamun S, Boyle KJ, Nolte C, Papenfus M, Polasky S. Spatial Heterogeneity in Hedonic Price Effects for Lake Water Quality. LAND ECONOMICS 2024; 100:89-108. [PMID: 38515763 PMCID: PMC10953790 DOI: 10.3368/le.100.1.102122-0086r] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
This study uses Zillow's ZTRAX property transaction database to investigate variation in hedonic price effects of water clarity on single-family houses throughout the United States. We consider five spatial scales and estimate models using different sample selection criteria and model specifications. Our results indicate considerable spatial heterogeneity both within and across the four U.S. Census regions. However, we also find heterogeneity resulting from different types of investigator decisions, including sample selection and modelling choices. Thus, it is necessary to use practical knowledge to consider the limits of market areas and to investigate the robustness of estimation results to investigator choices. (JEL Q51).
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Affiliation(s)
- Kristen Swedberg
- Department of Agricultural and Applied Economics, Virginia Tech, Blacksburg, VA
- ORISE Fellow in Office of Water, Environmental Protection Agency, Washington, DC
| | - Diego S Cardoso
- Department of Agricultural Economics, Purdue University, West Lafayette, IN
| | | | - Saleh Mamun
- Department of Applied Economics, University of Minnesota, St. Paul, MN
- The Natural Capital Project, University of Minnesota, St. Paul, MN
- Natural Resources Research Institute, University of Minnesota - Duluth, Duluth, MN
| | - Kevin J Boyle
- Department of Agricultural and Applied Economics, Virginia Tech, Blacksburg, VA
- Blackwood Department of Real Estate, Virginia Tech, Blacksburg, VA
| | - Christoph Nolte
- Department of Earth & Environment, Boston University, Boston, MA
- Faculty of Computing & Data Sciences, Boston University, Boston, MA
| | | | - Stephen Polasky
- Department of Applied Economics, University of Minnesota, St. Paul, MN
- The Natural Capital Project, University of Minnesota, St. Paul, MN
- Department of Ecology, Evolution & Behavior, University of Minnesota, St. Paul, MN
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2
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Kammerer M, Iverson AL, Li K, Goslee SC. Not just crop or forest: an integrated land cover map for agricultural and natural areas. Sci Data 2024; 11:137. [PMID: 38278830 PMCID: PMC10817889 DOI: 10.1038/s41597-024-02979-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 01/16/2024] [Indexed: 01/28/2024] Open
Abstract
Due to the key role surrounding landscape plays in ecological processes, a detailed characterization of land cover is critical for researchers and conservation practitioners. Unfortunately, in the United States, land cover data are split across thematic datasets that emphasize agricultural or natural vegetation, but not both. To address this gap, we merged two datasets, the LANDFIRE National Vegetation Classification (NVC) and USDA-NASS Cropland Data Layer (CDL), to produce integrated 'Spatial Products for Agriculture and Nature' (SPAN). Our workflow leveraged strengths of the NVC and the CDL to create detailed rasters comprising both agricultural and natural land-cover classes. We generated SPAN annually from 2012-2021 for the conterminous United States, quantified agreement and accuracy of SPAN, and published the complete computational workflow. In our validation analyses, we found that approximately 5.5% of NVC agricultural pixels conflicted with the CDL, but we resolved most conflicts, leaving only 0.6% of agricultural pixels unresolved in SPAN. These ready-to-use rasters characterizing both agricultural and natural land cover will be widely useful in environmental research and management.
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Affiliation(s)
- Melanie Kammerer
- USDA-ARS Pasture Systems and Watershed Management Research Unit, University Park, PA, 16802, USA.
- Oak Ridge Institute for Science and Education, Oak Ridge, TN, 37830, USA.
| | - Aaron L Iverson
- Department of Environmental Studies, St. Lawrence University, Canton, NY, 13617, USA
| | - Kevin Li
- School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Sarah C Goslee
- USDA-ARS Pasture Systems and Watershed Management Research Unit, University Park, PA, 16802, USA.
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3
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Cruz GLT, Winck GR, D'Andrea PS, Krempser E, Vidal MM, Andreazzi CS. Integrating databases for spatial analysis of parasite-host associations and the novel Brazilian dataset. Sci Data 2023; 10:757. [PMID: 37919263 PMCID: PMC10622529 DOI: 10.1038/s41597-023-02636-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 10/11/2023] [Indexed: 11/04/2023] Open
Abstract
Incomplete information on parasites, their associated hosts, and their precise geographical location hampers the ability to predict disease emergence in Brazil, a continental-sized country characterised by significant regional disparities. Here, we demonstrate how the NCBI Nucleotide and GBIF databases can be used as complementary databases to study spatially georeferenced parasite-host associations. We also provide a comprehensive dataset of parasites associated with mammal species that occur in Brazil, the Brazilian Mammal Parasite Occurrence Data (BMPO). This dataset integrates wild mammal species' morphological and life-history traits, zoonotic parasite status, and zoonotic microparasite transmission modes. Through meta-networks, comprising interconnected host species linked by shared zoonotic microparasites, we elucidate patterns of zoonotic microparasite dissemination. This approach contributes to wild animal and zoonoses surveillance, identifying and targeting host species accountable for disproportionate levels of parasite sharing within distinct biomes. Moreover, our novel dataset contributes to the refinement of models concerning disease emergence and parasite distribution among host species.
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Affiliation(s)
- Gabriella L T Cruz
- Laboratório de Biologia e Parasitologia de Mamíferos Silvestres Reservatórios (LABPMR), Instituto Oswaldo Cruz, Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, RJ, Brazil
- Programa de Pós-graduação em Biodiversidade e Saúde, Instituto Oswaldo Cruz (IOC), Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, RJ, Brazil
- Pró-Reitoria de Pós-Graduação, Pesquisa e Inovação (PROPGPI), Universidade Federal do Estado do Rio de Janeiro (Unirio), Rio de Janeiro, RJ, Brazil
| | - Gisele R Winck
- Laboratório de Biologia e Parasitologia de Mamíferos Silvestres Reservatórios (LABPMR), Instituto Oswaldo Cruz, Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, RJ, Brazil
| | - Paulo S D'Andrea
- Laboratório de Biologia e Parasitologia de Mamíferos Silvestres Reservatórios (LABPMR), Instituto Oswaldo Cruz, Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, RJ, Brazil
| | - Eduardo Krempser
- Plataforma Institucional Biodiversidade e Saúde Silvestre (PIBSS), Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, RJ, Brazil
| | - Mariana M Vidal
- Laboratório de Biologia e Parasitologia de Mamíferos Silvestres Reservatórios (LABPMR), Instituto Oswaldo Cruz, Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, RJ, Brazil
| | - Cecilia S Andreazzi
- Laboratório de Biologia e Parasitologia de Mamíferos Silvestres Reservatórios (LABPMR), Instituto Oswaldo Cruz, Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, RJ, Brazil.
- International Platform for Science, Technology and Innovation in Health (PICTIS), Ílhavo, Portugal.
- Departamento de Biodiversidad, Ecología y Evolución, Universidad Complutense de Madrid, Madrid, Spain.
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4
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Rose KC, Bierwagen B, Bridgham SD, Carlisle DM, Hawkins CP, Poff NL, Read JS, Rohr J, Saros JE, Williamson CE. Indicators of the effects of climate change on freshwater ecosystems. CLIMATIC CHANGE 2023; 173:1-20. [PMID: 39022649 PMCID: PMC11254324 DOI: 10.1007/s10584-022-03457-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Accepted: 10/12/2022] [Indexed: 07/20/2024]
Abstract
Freshwater ecosystems, including lakes, streams, and wetlands, are responsive to climate change and other natural and anthropogenic stresses. These ecosystems are frequently hydrologically and ecologically connected with one another and their surrounding landscapes, thereby integrating changes throughout their watersheds. The responses of any given freshwater ecosystem to climate change depend on the magnitude of climate forcing, interactions with other anthropogenic and natural changes, and the characteristics of the ecosystem itself. Therefore, the magnitude and manner in which freshwater ecosystems respond to climate change is difficult to predict a priori. We present a conceptual model to elucidate how freshwater ecosystems are altered by climate change. We identify eleven indicators that describe the response of freshwater ecosystems to climate change, discuss their potential value and limitations, and describe supporting measurements. Indicators are organized in three inter-related categories: hydrologic, water quality, and ecosystem structure and function. The indicators are supported by data sets with a wide range of temporal and spatial coverage, and they inform important scientific and management needs. Together, these indicators improve the understanding and management of the effects of climate change on freshwater ecosystems.
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Affiliation(s)
- Kevin C Rose
- Department of Biological Sciences, Rensselaer Polytechnic Institute
| | - Britta Bierwagen
- Center for Public Health and Environmental Assessment, Office of Research and Development, US Environmental Protection Agency
| | | | | | - Charles P Hawkins
- Department of Watershed Sciences, National Aquatic Monitoring Center, and the Ecology Center, Utah State University
| | - N LeRoy Poff
- Department of Biology, Colorado State University and Institute for Applied Ecology, University of Canberra
| | | | - Jason Rohr
- Department of Biological Sciences, Environmental Change Initiative, Eck Institute of Global Health, University of Notre Dame
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5
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Barber C, Zaiats A, Applestein C, Rosenthal L, Caughlin TT. Bayesian models for spatially explicit interactions between neighbouring plants. Methods Ecol Evol 2022. [DOI: 10.1111/2041-210x.13998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
| | - Andrii Zaiats
- Biological Sciences Boise State University Boise Idaho USA
| | - Cara Applestein
- Biological Sciences Boise State University Boise Idaho USA
- Forest and Rangeland Ecosystem Science Center U.S. Geological Survey Boise Idaho USA
| | - Lisa Rosenthal
- Department of Plant Pathology University of California Davis California USA
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6
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Midway SR, Sievert NA, Lynch AJ, Whittier JB, Pope KL. Asking nicely: Best practices for requesting data. ECOL INFORM 2022. [DOI: 10.1016/j.ecoinf.2022.101729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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7
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Schaeffer BA, Urquhart E, Coffer M, Salls W, Stumpf RP, Loftin KA, Werdell PJ. Satellites quantify the spatial extent of cyanobacterial blooms across the United States at multiple scales. ECOLOGICAL INDICATORS 2022; 140:1-14. [PMID: 36425672 PMCID: PMC9680831 DOI: 10.1016/j.ecolind.2022.108990] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Previous studies indicate that cyanobacterial harmful algal bloom (cyanoHAB) frequency, extent, and magnitude have increased globally over the past few decades. However, little quantitative capability is available to assess these metrics of cyanoHABs across broad geographic scales and at regular intervals. Here, the spatial extent was quantified from a cyanobacteria algorithm applied to two European Space Agency satellite platforms-the MEdium Resolution Imaging Spectrometer (MERIS) onboard Envisat and the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3. CyanoHAB spatial extent was defined for each geographic area as the percentage of valid satellite pixels that exhibited cyanobacteria above the detection limit of the satellite sensor. This study quantified cyanoHAB spatial extent for over 2,000 large lakes and reservoirs across the contiguous United States (CONUS) during two time periods: 2008-2011 via MERIS and 2017-2020 via OLCI when cloud-, ice-, and snow-free imagery was available. Approximately 56% of resolvable lakes were glaciated, 13% were headwater, isolated, or terminal lakes, and the rest were primarily drainage lakes. Results were summarized at national-, regional-, state-, and lake-scales, where regions were defined as nine climate regions which represent climatically consistent states. As measured by satellite, changes in national cyanoHAB extent did have a strong increase of 6.9% from 2017 to 2020 (|Kendall's tau (τ)| = 0.56; gamma (γ) = 2.87 years), but had negligible change (|τ| = 0.03) from 2008 to 2011. Two of the nine regions had moderate (0.3 ≤ |τ| < 0.5) increases in spatial extent from 2017 to 2020, and eight of nine regions had negligible (|τ| < 0.2) change from 2008 to 2011. Twelve states had a strong or moderate increase from 2017 to 2020 (|τ| ≥ 0.3), while only one state had a moderate increase and two states had a moderate decrease from 2008 to 2011. A decrease, or no change, in cyanoHAB spatial extent did not indicate a lack of issues related to cyanoHABs. Sensitivity results of randomly omitted daily CONUS scenes confirm that even with reduced data availability during a short four-year temporal assessment, the direction and strength of the changes in spatial extent remained consistent. We present the first set of national maps of lake cyanoHAB spatial extent across CONUS and demonstrate an approach for quantifying past and future changes at multiple spatial scales. Results presented here provide water quality managers information regarding current cyanoHAB spatial extent and quantify rates of change.
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Affiliation(s)
- Blake A. Schaeffer
- Office of Research and Development, U.S. Environmental Protection Agency, 109 T.W. Alexander Drive, Durham, NC 27709, United States
| | - Erin Urquhart
- Science Systems and Applications, Inc., Ocean Ecology Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, United States
| | - Megan Coffer
- Oak Ridge Institute for Science and Education (ORISE), U.S. Environmental Protection Agency, 109 T.W. Alexander Drive, Durham, NC 27709, United States
| | - Wilson Salls
- Office of Research and Development, U.S. Environmental Protection Agency, 109 T.W. Alexander Drive, Durham, NC 27709, United States
| | - Richard P. Stumpf
- National Oceanic and Atmospheric Administration, National Centers for Coastal Ocean Science, 1305 East-West Highway Code N/SCI1, Silver Spring, MD 20910, United States
| | - Keith A. Loftin
- U.S. Geological Survey, Organic Geochemistry Research Laboratory, Kansas Water Science Center, 1217 Biltmore Drive, Lawrence, KS 66049, United States
| | - P. Jeremy Werdell
- Ocean Ecology Laboratory, NASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771, United States
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8
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Igumbor JO, Bosire EN, Vicente-Crespo M, Igumbor EU, Olalekan UA, Chirwa TF, Kinyanjui SM, Kyobutungi C, Fonn S. Considerations for an integrated population health databank in Africa: lessons from global best practices. Wellcome Open Res 2022; 6:214. [PMID: 35224211 PMCID: PMC8844538 DOI: 10.12688/wellcomeopenres.17000.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/12/2021] [Indexed: 12/17/2022] Open
Abstract
Background: The rising digitisation and proliferation of data sources and repositories cannot be ignored. This trend expands opportunities to integrate and share population health data. Such platforms have many benefits, including the potential to efficiently translate information arising from such data to evidence needed to address complex global health challenges. There are pockets of quality data on the continent that may benefit from greater integration. Integration of data sources is however under-explored in Africa. The aim of this article is to identify the requirements and provide practical recommendations for developing a multi-consortia public and population health data-sharing framework for Africa. Methods: We conducted a narrative review of global best practices and policies on data sharing and its optimisation. We searched eight databases for publications and undertook an iterative snowballing search of articles cited in the identified publications. The Leximancer software
© enabled content analysis and selection of a sample of the most relevant articles for detailed review. Themes were developed through immersion in the extracts of selected articles using inductive thematic analysis. We also performed interviews with public and population health stakeholders in Africa to gather their experiences, perceptions, and expectations of data sharing. Results: Our findings described global stakeholder experiences on research data sharing. We identified some challenges and measures to harness available resources and incentivise data sharing. We further highlight progress made by the different groups in Africa and identified the infrastructural requirements and considerations when implementing data sharing platforms. Furthermore, the review suggests key reforms required, particularly in the areas of consenting, privacy protection, data ownership, governance, and data access. Conclusions: The findings underscore the critical role of inclusion, social justice, public good, data security, accountability, legislation, reciprocity, and mutual respect in developing a responsive, ethical, durable, and integrated research data sharing ecosystem.
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Affiliation(s)
- Jude O Igumbor
- School of Public Health, University of the Witwatersrand, Johannesburg, Gauteng, 2193, South Africa
| | - Edna N Bosire
- School of Public Health, University of the Witwatersrand, Johannesburg, Gauteng, 2193, South Africa
| | - Marta Vicente-Crespo
- School of Public Health, University of the Witwatersrand, Johannesburg, Gauteng, 2193, South Africa.,African Population and Health Research Centre, Nairobi, Kenya
| | - Ehimario U Igumbor
- Nigeria Centre for Disease Control, Abuja, Nigeria.,School of Public Health, University of the Western Cape, Cape Town, Western Cape, South Africa
| | - Uthman A Olalekan
- Warwick-Centre for Applied Health Research and Delivery (WCAHRD), Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK
| | - Tobias F Chirwa
- School of Public Health, University of the Witwatersrand, Johannesburg, Gauteng, 2193, South Africa
| | | | | | - Sharon Fonn
- School of Public Health, University of the Witwatersrand, Johannesburg, Gauteng, 2193, South Africa
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9
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Narr CF, Chernyavskiy P, Collins SM. Partitioning macroscale and microscale ecological processes using covariate-driven non-stationary spatial models. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2022; 32:e02485. [PMID: 34676934 DOI: 10.1002/eap.2485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 03/31/2021] [Accepted: 05/18/2021] [Indexed: 06/13/2023]
Abstract
Ecological inference requires integrating information across scales. This integration creates a complex spatial dependence structure that is most accurately represented by fully non-stationary models. However, ecologists rarely use these models because they are difficult to estimate and interpret. Here, we facilitate the use of fully non-stationary models in ecology by improving the interpretability of a recently developed non-stationary model and applying it to improve our understanding of the spatial processes driving lake eutrophication. We reformulated a model that incorporates non-stationary correlation by adding environmental predictors to the covariance function, thereby building on the intuition of mean regression. We created ellipses to visualize how data at a given site correlate with their surroundings (i.e., the range and directionality of underlying spatial processes). We applied this model to describe the spatial dependence structure of variables related to lake eutrophication across two different regions: a Midwestern United States region with highly agricultural landscapes, and a Northeastern United States region with heterogeneous land use. For the Midwest, increases in forest cover increased the homogeneity of the residual spatial structure of total phosphorus, indicating that macroscale processes dominated this nutrient's spatial structure. Conversely, high forest cover and baseflow reduced the spatial homogeneity of chlorophyll a residuals, indicating that microscale processes dominated for chlorophyll a in the Midwest. In the Northeast, increases in urban land use and baseflow decreased the homogeneity of phosphorus concentrations indicating the dominance of microscale processes, but none of our covariates were strongly associated with the residual spatial structure of chlorophyll a. Our model showed that the spatial dependence structure of environmental response variables shifts across space. It also helped to explain this structure using ecologically relevant covariates from different scales whose effects can be interpreted intuitively. This provided novel insight into the processes that lead to eutrophication, a complex and pervasive environmental issue.
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Affiliation(s)
- Charlotte F Narr
- Southern Illinois University in Carbondale, Carbondale, Illinois, 62901, USA
- Department of Zoology and Physiology, University of Wyoming, Laramie, Wyoming, 82071, USA
| | - Pavel Chernyavskiy
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, 22903, USA
| | - Sarah M Collins
- Department of Zoology and Physiology, University of Wyoming, Laramie, Wyoming, 82071, USA
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10
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Carleton JN, Washington BJ. Assessing Evidence of Phosphorus Concentration Trends in North American Fresh Waters. JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION 2021; 57:956-971. [PMID: 36960312 PMCID: PMC10031499 DOI: 10.1111/1752-1688.12970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Accepted: 10/13/2021] [Indexed: 06/18/2023]
Abstract
The U.S. EPA's National Aquatic Resource Surveys (NARS) documented evidence of widespread, unexplained total phosphorus (TP) concentration increases in lakes and streams across the United States during the 2000 - 2012 time period. To examine the robustness of evidence for this trend, we used additional monitoring datasets to calculate rates of TP change in thousands of individual waterbodies across the U.S. during the same time frame, and compared them against TP change rates calculated in the same manner for waterbodies that were resurveyed under NARS in different years. For the additional datasets, median rates of TP change were substantially lower than median rates calculated using NARS data. To further examine differences between NARS and non-NARS results in specific waterbodies, we assembled composite datasets for 52 predominantly northern lakes that by chance had been sampled under both NARS and other sampling programs during the same time frame. Using only NARS data, the median calculated TP change rate for this set of lakes was positive, and similar to that for the larger set of 401 resurveyed NARS lakes. However, when additional sample data were included, the median calculated TP change rate for these lakes was much lower. Results suggest that increasing TP concentrations in waterbodies may not have been as ubiquitous as suggested. They also illustrate a need to supplement randomized continental-scale monitoring with detailed, site-focused investigations.
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Affiliation(s)
- James N. Carleton
- Office of Research and Development, Center for Public Health and Environmental Assessment, U.S. Environmental Protection Agency (Mail Code 8623R), 1200 Pennsylvania Ave NW, Washington, DC
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11
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Introducing an Open-Source Regional Water Quality Data Viewer Tool to Support Research Data Access. HYDROLOGY 2021. [DOI: 10.3390/hydrology8020091] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Water quality data collection, storage, and access is a difficult task and significant work has gone into methods to store and disseminate these data. We present a tool to disseminate research in a simple method that does not replace but extends and leverages these tools. The tool is not geo-graphically limited and works with any spatially-referenced data. In most regions, government agencies maintain central repositories for water quality data. In the United States, the federal government maintains two systems to fill that role for hydrological data: the U.S. Geological Survey (USGS) National Water Information System (NWIS) and the U.S. Environmental Protection Agency (EPA) Storage and Retrieval System (STORET), since superseded by the Water Quality Portal (WQP). The Consortium of the Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) has developed the Hydrologic Information System (HIS) to standardize the search and discovery of these data as well as other observational time series datasets. Additionally, CUAHSI developed and maintains HydroShare.org (5 May 2021) as a web portal for researchers to store and share hydrology data in a variety of formats including spatial geographic information system data. We present the Tethys Platform based Water Quality Data Viewer (WQDV) web application that uses these systems to provide researchers and local monitoring organizations with a simple method to archive, view, analyze, and distribute water quality data. WQDV provides an archive for non-official or preliminary research data and access to those data that have been collected but need to be distributed prior to review or inclusion in the state database. WQDV can also accept subsets of data downloaded from other sources, such as the EPA WQP. WQDV helps users understand what local data are available and how they relate to the data in larger databases. WQDV presents data in spatial (maps) and temporal (time series graphs) forms to help the users analyze and potentially screen the data sources before export for additional analysis. WQDV provides a convenient method for interim data to be widely disseminated and easily accessible in the context of a subset of official data. We present WQDV using a case study of data from Utah Lake, Utah, United States of America.
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12
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Hollister JW, Kellogg DQ, Kreakie BJ, Shivers SD, Milstead WB, Herron EM, Green LT, Gold AJ. Analyzing long-term water quality of lakes in Rhode Island and the northeastern United States with an anomaly approach. Ecosphere 2021; 12:10.1002/ecs2.3555. [PMID: 34249403 PMCID: PMC8262619 DOI: 10.1002/ecs2.3555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 01/12/2021] [Indexed: 11/09/2022] Open
Abstract
Addressing anthropogenic impacts on aquatic ecosystems is a focus of lake management. Controlling phosphorus and nitrogen can mitigate these impacts, but determining management effectiveness requires long-term datasets. Recent analysis of the LAke multi-scaled GeOSpatial and temporal database for the Northeast (LAGOS-NE) United States found stable water quality in the northeastern and midwestern United States; however, sub-regional trends may be obscured. We used the University of Rhode Island's Watershed Watch Volunteer Monitoring Program (URIWW) dataset to determine if there were sub-regional (i.e., 3000 km2) water quality trends. URIWW has collected water quality data on Rhode Island lakes and reservoirs for over 25 yr. The LAGOS-NE and URIWW datasets allowed for comparison of water quality trends at regional and sub-regional scales, respectively. We assessed regional (LAGOS-NE) and sub-regional (URIWW) trends with yearly median anomalies calculated on a per-station basis. Sub-regionally, temperature and chlorophyll a increased from 1993 to 2016. Total nitrogen, total phosphorus, and the nitrogen:phosphorus ratio (N:P) were stable. At the regional scale, the LAGOS-NE dataset showed similar trends to prior studies of the LAGOS-NE with chlorophyll a, total nitrogen, and N:P all stable over time. Total phosphorus did show a very slight increase. In short, algal biomass, as measured by chlorophyll a in Rhode Island lakes and reservoirs increased, despite stability in total nitrogen, total phosphorus, and the nitrogen to phosphorus ratio. Additionally, we demonstrated both the value of long-term monitoring programs, like URIWW, for identifying trends in environmental condition, and the utility of site-specific anomalies for analyzing for long-term water quality trends.
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Affiliation(s)
- J. W. Hollister
- U.S. Environmental Protection Agency, Office of Research and Development, Atlantic Coastal Environmental Sciences Division, Narragansett, Rhode Island 02882 USA
| | - D. Q. Kellogg
- Department of Natural Resources Science, University of Rhode Island, Kingston, Rhode Island 02881 USA
| | - B. J. Kreakie
- U.S. Environmental Protection Agency, Office of Research and Development, Atlantic Coastal Environmental Sciences Division, Narragansett, Rhode Island 02882 USA
| | - S. D. Shivers
- U.S. Environmental Protection Agency, Office of Research and Development, Atlantic Coastal Environmental Sciences Division, Narragansett, Rhode Island 02882 USA
| | - W. B. Milstead
- U.S. Environmental Protection Agency, Office of Research and Development, Atlantic Coastal Environmental Sciences Division, Narragansett, Rhode Island 02882 USA
| | - E. M. Herron
- Department of Natural Resources Science, University of Rhode Island, Kingston, Rhode Island 02881 USA
| | - L. T. Green
- Department of Natural Resources Science, University of Rhode Island, Kingston, Rhode Island 02881 USA
| | - A. J. Gold
- Department of Natural Resources Science, University of Rhode Island, Kingston, Rhode Island 02881 USA
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13
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Bond-Lamberty B, Christianson DS, Crystal-Ornelas R, Mathes K, Pennington SC. A reporting format for field measurements of soil respiration. ECOL INFORM 2021. [DOI: 10.1016/j.ecoinf.2021.101280] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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14
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Lapierre J, Collins SM, Oliver SK, Stanley EH, Wagner T. Inconsistent browning of northeastern U.S. lakes despite increased precipitation and recovery from acidification. Ecosphere 2021. [DOI: 10.1002/ecs2.3415] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- Jean‐Francois Lapierre
- Département de sciences biologiques Université de Montréal Montréal QuébecH3C 3J7Canada
- Groupe de Recherche Interuniversitaire en Limnologie (GRIL) Université du Québec à Montréal Montréal QuebecH3C 3P8Canada
| | - Sarah M. Collins
- Department of Zoology and Physiology University of Wyoming Laramie Wyoming82701USA
- Program in Ecology University of Wyoming Laramie Wyoming82701USA
| | - Samantha K. Oliver
- U.S. Geological Survey Upper Midwest Water Science Center Middleton Wisconsin53562USA
| | - Emily H. Stanley
- Center for Limnology University of Wisconsin‐Madison Madison Wisconsin53706USA
| | - Tyler Wagner
- U.S. Geological Survey Pennsylvania Cooperative Fish and Wildlife Unit The Pennsylvania State University University Park Pennsylvania16802USA
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15
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Harker KJ, Arnold L, Sutherland IJ, Gergel SE. Perspectives from landscape ecology can improve environmental impact assessment. Facets (Ott) 2021. [DOI: 10.1139/facets-2020-0049] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The outcomes of environmental impact assessment (EIA) influence millions of hectares of land and can be a contentious process. A vital aspect of an EIA process is consideration of the accumulation of impacts from multiple activities and stressors through a cumulative effects assessment (CEA). An opportunity exists to improve the rigor and utility of CEA and EIA by incorporating core scientific principles of landscape ecology into EIA. With examples from a Canadian context, we explore realistic hypothetical situations demonstrating how integration of core scientific principles could impact EIA outcomes. First, we demonstrate how changing the spatial extent of EIA boundaries can misrepresent cumulative impacts via the exclusion or inclusion of surrounding natural resource development projects. Second, we use network analysis to show how even a seemingly small, localized development project can disrupt regional habitat connectivity. Lastly, we explore the benefits of using long-term historical remote sensing products. Because these approaches are straightforward to implement using publicly available data, they provide sensible opportunities to improve EIA and enhance the monitoring of natural resource development activities in Canada and elsewhere.
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Affiliation(s)
- Karly J. Harker
- Department of Forest and Conservation Sciences, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada
| | - Lauren Arnold
- Centre for Environmental Assessment Research, Fipke Centre, University of British Columbia—Okanagan Campus, 246, 3427 University Way, Kelowna, BC V1V 1V7, Canada
| | - Ira J. Sutherland
- Department of Forest and Conservation Sciences, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada
| | - Sarah E. Gergel
- Department of Forest and Conservation Sciences, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada
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16
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Schliep EM, Collins SM, Rojas-Salazar S, Lottig NR, Stanley EH. Data fusion model for speciated nitrogen to identify environmental drivers and improve estimation of nitrogen in lakes. Ann Appl Stat 2020. [DOI: 10.1214/20-aoas1371] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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17
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Sielemann K, Hafner A, Pucker B. The reuse of public datasets in the life sciences: potential risks and rewards. PeerJ 2020; 8:e9954. [PMID: 33024631 PMCID: PMC7518187 DOI: 10.7717/peerj.9954] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 08/25/2020] [Indexed: 12/13/2022] Open
Abstract
The 'big data' revolution has enabled novel types of analyses in the life sciences, facilitated by public sharing and reuse of datasets. Here, we review the prodigious potential of reusing publicly available datasets and the associated challenges, limitations and risks. Possible solutions to issues and research integrity considerations are also discussed. Due to the prominence, abundance and wide distribution of sequencing data, we focus on the reuse of publicly available sequence datasets. We define 'successful reuse' as the use of previously published data to enable novel scientific findings. By using selected examples of successful reuse from different disciplines, we illustrate the enormous potential of the practice, while acknowledging the respective limitations and risks. A checklist to determine the reuse value and potential of a particular dataset is also provided. The open discussion of data reuse and the establishment of this practice as a norm has the potential to benefit all stakeholders in the life sciences.
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Affiliation(s)
- Katharina Sielemann
- Genetics and Genomics of Plants, Center for Biotechnology (CeBiTec) & Faculty of Biology, Bielefeld University, Bielefeld, Germany
- Graduate School DILS, Bielefeld Institute for Bioinformatics Infrastructure (BIBI), Bielefeld University, Bielefeld, Germany
| | - Alenka Hafner
- Genetics and Genomics of Plants, Center for Biotechnology (CeBiTec) & Faculty of Biology, Bielefeld University, Bielefeld, Germany
- Current Affiliation: Intercollege Graduate Degree Program in Plant Biology, Penn State University, University Park, State College, PA, United States of America
| | - Boas Pucker
- Genetics and Genomics of Plants, Center for Biotechnology (CeBiTec) & Faculty of Biology, Bielefeld University, Bielefeld, Germany
- Evolution and Diversity, Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom
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18
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Soranno PA, Cheruvelil KS, Liu B, Wang Q, Tan PN, Zhou J, King KBS, McCullough IM, Stachelek J, Bartley M, Filstrup CT, Hanks EM, Lapierre JF, Lottig NR, Schliep EM, Wagner T, Webster KE. Ecological prediction at macroscales using big data: Does sampling design matter? ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2020; 30:e02123. [PMID: 32160362 DOI: 10.1002/eap.2123] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Revised: 12/13/2019] [Accepted: 01/06/2020] [Indexed: 06/10/2023]
Abstract
Although ecosystems respond to global change at regional to continental scales (i.e., macroscales), model predictions of ecosystem responses often rely on data from targeted monitoring of a small proportion of sampled ecosystems within a particular geographic area. In this study, we examined how the sampling strategy used to collect data for such models influences predictive performance. We subsampled a large and spatially extensive data set to investigate how macroscale sampling strategy affects prediction of ecosystem characteristics in 6,784 lakes across a 1.8-million-km2 area. We estimated model predictive performance for different subsets of the data set to mimic three common sampling strategies for collecting observations of ecosystem characteristics: random sampling design, stratified random sampling design, and targeted sampling. We found that sampling strategy influenced model predictive performance such that (1) stratified random sampling designs did not improve predictive performance compared to simple random sampling designs and (2) although one of the scenarios that mimicked targeted (non-random) sampling had the poorest performing predictive models, the other targeted sampling scenarios resulted in models with similar predictive performance to that of the random sampling scenarios. Our results suggest that although potential biases in data sets from some forms of targeted sampling may limit predictive performance, compiling existing spatially extensive data sets can result in models with good predictive performance that may inform a wide range of science questions and policy goals related to global change.
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Affiliation(s)
- Patricia A Soranno
- Department of Fisheries and Wildlife, Michigan State University, 480 Wilson Road, East Lansing, Michigan, 48824, USA
| | - Kendra Spence Cheruvelil
- Department of Fisheries and Wildlife, Michigan State University, 480 Wilson Road, East Lansing, Michigan, 48824, USA
- Lyman Briggs College, Michigan State University, 919 East Shaw Lane, East Lansing, Michigan, 48825, USA
| | - Boyang Liu
- Department of Computer Science and Engineering, Michigan State University, 428 South Shaw Lane, East Lansing, Michigan, 48824, USA
| | - Qi Wang
- Department of Computer Science and Engineering, Michigan State University, 428 South Shaw Lane, East Lansing, Michigan, 48824, USA
| | - Pang-Ning Tan
- Department of Computer Science and Engineering, Michigan State University, 428 South Shaw Lane, East Lansing, Michigan, 48824, USA
| | - Jiayu Zhou
- Department of Computer Science and Engineering, Michigan State University, 428 South Shaw Lane, East Lansing, Michigan, 48824, USA
| | - Katelyn B S King
- Department of Fisheries and Wildlife, Michigan State University, 480 Wilson Road, East Lansing, Michigan, 48824, USA
| | - Ian M McCullough
- Department of Fisheries and Wildlife, Michigan State University, 480 Wilson Road, East Lansing, Michigan, 48824, USA
| | - Joseph Stachelek
- Department of Fisheries and Wildlife, Michigan State University, 480 Wilson Road, East Lansing, Michigan, 48824, USA
| | - Meridith Bartley
- Department of Statistics, The Pennsylvania State University, 324 Thomas Building, University Park, Pennsylvania, 16802, USA
| | - Christopher T Filstrup
- Natural Resources Research Institute, University of Minnesota Duluth, 5013 Miller Trunk Highway, Duluth, Minnesota, 55811, USA
| | - Ephraim M Hanks
- Department of Statistics, The Pennsylvania State University, 324 Thomas Building, University Park, Pennsylvania, 16802, USA
| | - Jean-François Lapierre
- Sciences Biologiques, Universite de Montreal, Pavillon Marie-Victorin, CP 6128, succursale Centre-Ville, Montreal, Quebec, H3C 3J7, Canada
| | - Noah R Lottig
- Center for Limnology Trout Lake Station, University of Wisconsin Madison, Boulder Junction, Wisconsin, 54512, USA
| | - Erin M Schliep
- Department of Statistics, University of Missouri, 146 Middlebush Hall, Columbia, Missouri, 65211, USA
| | - Tyler Wagner
- U.S. Geological Survey, Pennsylvania Cooperative Fish and Wildlife Research Unit, Pennsylvania State University, Forest Resources Building, University Park, Pennsylvania, 16802, USA
| | - Katherine E Webster
- Department of Fisheries and Wildlife, Michigan State University, 480 Wilson Road, East Lansing, Michigan, 48824, USA
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19
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Meyer MF, Labou SG, Cramer AN, Brousil MR, Luff BT. The global lake area, climate, and population dataset. Sci Data 2020; 7:174. [PMID: 32528065 PMCID: PMC7289843 DOI: 10.1038/s41597-020-0517-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Accepted: 05/11/2020] [Indexed: 11/11/2022] Open
Abstract
An increasing population in conjunction with a changing climate necessitates a detailed understanding of water abundance at multiple spatial and temporal scales. Remote sensing has provided massive data volumes to track fluctuations in water quantity, yet contextualizing water abundance with other local, regional, and global trends remains challenging by often requiring large computational resources to combine multiple data sources into analytically-friendly formats. To bridge this gap and facilitate future freshwater research opportunities, we harmonized existing global datasets to create the Global Lake area, Climate, and Population (GLCP) dataset. The GLCP is a compilation of lake surface area for 1.42 + million lakes and reservoirs of at least 10 ha in size from 1995 to 2015 with co-located basin-level temperature, precipitation, and population data. The GLCP was created with FAIR (findable, accessible, interoperable, reusable) data principles in mind and retains unique identifiers from parent datasets to expedite interoperability. The GLCP offers critical data for basic and applied investigations of lake surface area and water quantity at local, regional, and global scales. Measurement(s) | area of open water • temperature of air • volume of hydrological precipitation • population | Technology Type(s) | digital curation | Factor Type(s) | year • geographic location | Sample Characteristic - Environment | lake |
Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12328214
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Affiliation(s)
- Michael F Meyer
- School of the Environment, Washington State University, Pullman, Washington, 99164, USA.
| | - Stephanie G Labou
- Center for Environmental Research, Education, and Outreach, Washington State University, Pullman, Washington, 99164, USA.,University of California San Diego, La Jolla, California, 92093, USA
| | - Alli N Cramer
- School of the Environment, Washington State University, Pullman, Washington, 99164, USA
| | - Matthew R Brousil
- Center for Environmental Research, Education, and Outreach, Washington State University, Pullman, Washington, 99164, USA
| | - Bradley T Luff
- School of the Environment, Washington State University, Pullman, Washington, 99164, USA
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20
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Fergus CE, Brooks JR, Kaufmann PR, Herlihy AT, Pollard AI, Weber MH, Paulsen SG. Lake Water Levels and Associated Hydrologic Characteristics in the Conterminous U.S. JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION 2020; 56:450-471. [PMID: 32699495 PMCID: PMC7375517 DOI: 10.1111/1752-1688.12817] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2019] [Accepted: 11/14/2019] [Indexed: 05/19/2023]
Abstract
Establishing baseline hydrologic characteristics for lakes in the U.S. is critical to evaluate changes to lake hydrology. We used the U.S. EPA National Lakes Assessment 2007 and 2012 surveys to assess hydrologic characteristics of a population of ~45,000 lakes in the conterminous U.S. based on probability samples of ~1,000 lakes/yr distributed across nine ecoregions. Lake hydrologic study variables include water-level drawdown (i.e., vertical decline and horizontal littoral exposure) and two water stable isotope-derived parameters: evaporation-to-inflow (E:I) and water residence time. We present 1) national and regional distributions of the study variables for both natural and man-made lakes and 2) differences in these characteristics between 2007 and 2012. In 2007, 59% of the population of U.S. lakes had Greater than normal or Excessive drawdown relative to water levels in ecoregional reference lakes with minimal human disturbances; while in 2012, only 20% of lakes were significantly drawn down beyond normal ranges. Water isotope-derived variables did not differ significantly between survey years in contrast to drawdown. Median E:I was 20% indicating that flow-through processes dominated lake water regimes. For 75% of U.S. lakes, water residence time was < 1 year and was longer in natural vs. man-made lakes. Our study provides baseline ranges to assess local and regional lake hydrologic status and inform management decisions in changing environmental conditions.
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Affiliation(s)
- C Emi Fergus
- National Research Council (Fergus, Herlihy), U.S. Environmental Protection Agency, Corvallis, Oregon, USA; Pacific Ecological Systems Division (Brooks, Kaufmann, Weber, Paulsen), U.S. Environmental Protection Agency, Corvallis, Oregon, USA; Office of Water (Pollard), U.S. Environmental Protection Agency, Washington, DC, USA
| | - J Renée Brooks
- National Research Council (Fergus, Herlihy), U.S. Environmental Protection Agency, Corvallis, Oregon, USA; Pacific Ecological Systems Division (Brooks, Kaufmann, Weber, Paulsen), U.S. Environmental Protection Agency, Corvallis, Oregon, USA; Office of Water (Pollard), U.S. Environmental Protection Agency, Washington, DC, USA
| | - Philip R Kaufmann
- National Research Council (Fergus, Herlihy), U.S. Environmental Protection Agency, Corvallis, Oregon, USA; Pacific Ecological Systems Division (Brooks, Kaufmann, Weber, Paulsen), U.S. Environmental Protection Agency, Corvallis, Oregon, USA; Office of Water (Pollard), U.S. Environmental Protection Agency, Washington, DC, USA
| | - Alan T Herlihy
- National Research Council (Fergus, Herlihy), U.S. Environmental Protection Agency, Corvallis, Oregon, USA; Pacific Ecological Systems Division (Brooks, Kaufmann, Weber, Paulsen), U.S. Environmental Protection Agency, Corvallis, Oregon, USA; Office of Water (Pollard), U.S. Environmental Protection Agency, Washington, DC, USA
| | - Amina I Pollard
- National Research Council (Fergus, Herlihy), U.S. Environmental Protection Agency, Corvallis, Oregon, USA; Pacific Ecological Systems Division (Brooks, Kaufmann, Weber, Paulsen), U.S. Environmental Protection Agency, Corvallis, Oregon, USA; Office of Water (Pollard), U.S. Environmental Protection Agency, Washington, DC, USA
| | - Marc H Weber
- National Research Council (Fergus, Herlihy), U.S. Environmental Protection Agency, Corvallis, Oregon, USA; Pacific Ecological Systems Division (Brooks, Kaufmann, Weber, Paulsen), U.S. Environmental Protection Agency, Corvallis, Oregon, USA; Office of Water (Pollard), U.S. Environmental Protection Agency, Washington, DC, USA
| | - Steven G Paulsen
- National Research Council (Fergus, Herlihy), U.S. Environmental Protection Agency, Corvallis, Oregon, USA; Pacific Ecological Systems Division (Brooks, Kaufmann, Weber, Paulsen), U.S. Environmental Protection Agency, Corvallis, Oregon, USA; Office of Water (Pollard), U.S. Environmental Protection Agency, Washington, DC, USA
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21
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Ochs AR, Mehrabi M, Becker D, Asad MN, Zhao J, Zaragoza MV, Grosberg A. Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering. J Vis Exp 2019. [PMID: 31814616 DOI: 10.3791/60038] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Science relies on increasingly complex data sets for progress, but common data management methods such as spreadsheet programs are inadequate for the growing scale and complexity of this information. While database management systems have the potential to rectify these issues, they are not commonly utilized outside of business and informatics fields. Yet, many research labs already generate "medium sized", low velocity, multi-dimensional data that could greatly benefit from implementing similar systems. In this article, we provide a conceptual overview explaining how databases function and the advantages they provide in tissue engineering applications. Structural fibroblast data from individuals with a lamin A/C mutation was used to illustrate examples within a specific experimental context. Examples include visualizing multidimensional data, linking tables in a relational database structure, mapping a semi-automated data pipeline to convert raw data into structured formats, and explaining the underlying syntax of a query. Outcomes from analyzing the data were used to create plots of various arrangements and significance was demonstrated in cell organization in aligned environments between the positive control of Hutchinson-Gilford progeria, a well-known laminopathy, and all other experimental groups. In comparison to spreadsheets, database methods were enormously time efficient, simple to use once set up, allowed for immediate access of original file locations, and increased data rigor. In response to the National Institutes of Health (NIH) emphasis on experimental rigor, it is likely that many scientific fields will eventually adopt databases as common practice due to their strong capability to effectively organize complex data.
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Affiliation(s)
- Alexander R Ochs
- Department of Biomedical Engineering, University of California, Irvine; The Edwards Lifesciences Center for Advanced Cardiovascular Technology, University of California, Irvine
| | - Mehrsa Mehrabi
- Department of Biomedical Engineering, University of California, Irvine; The Edwards Lifesciences Center for Advanced Cardiovascular Technology, University of California, Irvine
| | - Danielle Becker
- Department of Biomedical Engineering, University of California, Irvine; The Edwards Lifesciences Center for Advanced Cardiovascular Technology, University of California, Irvine
| | - Mira N Asad
- Department of Biomedical Engineering, University of California, Irvine; The Edwards Lifesciences Center for Advanced Cardiovascular Technology, University of California, Irvine
| | - Jing Zhao
- Department of Biomedical Engineering, University of California, Irvine; The Edwards Lifesciences Center for Advanced Cardiovascular Technology, University of California, Irvine
| | - Michael V Zaragoza
- Pediatrics-Genetics & Genomics Division-School of Medicine, University of California, Irvine; Biological Chemistry-School of Medicine, University of California, Irvine
| | - Anna Grosberg
- Department of Biomedical Engineering, University of California, Irvine; The Edwards Lifesciences Center for Advanced Cardiovascular Technology, University of California, Irvine; Department of Chemical and Biomolecular Engineering, University of California, Irvine; Center for Complex Biological Systems, University of California, Irvine; The NSF-Simons Center for Multiscale Cell Fate Research (CMCF), University of California, Irvine;
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22
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Soranno PA, Wagner T, Collins SM, Lapierre JF, Lottig NR, Oliver SK. Spatial and temporal variation of ecosystem properties at macroscales. Ecol Lett 2019; 22:1587-1598. [PMID: 31347258 DOI: 10.1111/ele.13346] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 06/03/2019] [Accepted: 06/26/2019] [Indexed: 01/16/2023]
Abstract
Although spatial and temporal variation in ecological properties has been well-studied, crucial knowledge gaps remain for studies conducted at macroscales and for ecosystem properties related to material and energy. We test four propositions of spatial and temporal variation in ecosystem properties within a macroscale (1000 km's) extent. We fit Bayesian hierarchical models to thousands of observations from over two decades to quantify four components of variation - spatial (local and regional) and temporal (local and coherent); and to model their drivers. We found strong support for three propositions: (1) spatial variation at local and regional scales are large and roughly equal, (2) annual temporal variation is mostly local rather than coherent, and, (3) spatial variation exceeds temporal variation. Our findings imply that predicting ecosystem responses to environmental changes at macroscales requires consideration of the dominant spatial signals at both local and regional scales that may overwhelm temporal signals.
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Affiliation(s)
- Patricia A Soranno
- Department of Fisheries and Wildlife, Michigan St. University, 480 Wilson Rd, East Lansing, MI, 48824, USA
| | - Tyler Wagner
- U.S. Geological Survey, Pennsylvania Cooperative Fish & Wildlife Research Unit, Pennsylvania State University, 402 Forest Resources Building, University Park, PA, 16802, USA
| | - Sarah M Collins
- Department of Zoology and Physiology, University of Wyoming, Laramie, WY, 82071, USA
| | - Jean-Francois Lapierre
- Department of Biological Science, University of Montreal, Montreal, Quebec, Canada, H3C 3J7
| | - Noah R Lottig
- Trout Lake Research Station, Univ. of Wisconsin, 3110 Trout Lake Station Drive, Boulder Junction, WI, 54512, USA
| | - Samantha K Oliver
- Upper Midwest Water Science Center, U.S. Geological Survey, 8505 Research Way, Middleton, WI, 53562, USA
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23
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McCullough IM, Cheruvelil KS, Collins SM, Soranno PA. Geographic patterns of the climate sensitivity of lakes. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2019; 29:e01836. [PMID: 30644621 DOI: 10.1002/eap.1836] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Revised: 10/16/2018] [Accepted: 11/13/2018] [Indexed: 05/22/2023]
Abstract
Climate change is a well-recognized threat to lake ecosystems and, although there likely exists geographic variation in the sensitivity of lakes to climate, broad-scale, long-term studies are needed to understand this variation. Further, the potential mediating role of local to regional ecological context on these responses is not well documented. In this study, we examined relationships between climate and water clarity in 365 lakes from 1981 to 2010 in two distinct regions in the northeastern and midwestern United States. We asked (1) How do climate-water-clarity relationships vary across watersheds and between two geographic regions? and (2) Do certain characteristics make some lakes more climate sensitive than others? We found strong differences in climate-water-clarity relationships both within and across the two regions. For example, in the northeastern region, water clarity was often negatively correlated with summer precipitation (median correlation = -0.32, n = 160 lakes), but was not correlated with summer average maximum temperature (median correlation = 0.09, n = 205 lakes). In the midwestern region, water clarity was not related to summer precipitation (median correlation = -0.04), but was often negatively correlated with summer average maximum temperature (median correlation = -0.18). There were few strong relationships between local and sub-regional ecological context and a lake's sensitivity to climate. For example, ecological context variables explained just 16-18% of variation in summer precipitation sensitivity, which was most related to total phosphorus, chlorophyll a, lake depth, and hydrology in both regions. Sensitivity to summer maximum temperature was even less predictable in both regions, with 4% or less of variation explained using all ecological context variables. Overall, we identified differences in the climate sensitivity of lakes across regions and found that local and sub-regional ecological context weakly influences the sensitivity of lakes to climate. Our findings suggest that local to regional drivers may combine to influence the sensitivity of lake ecosystems to climate change, and that sensitivities among lakes are highly variable within and across regions. This variability suggests that lakes are sensitive to different aspects of climate change (temperature vs. precipitation) and that responses of lakes to climate are heterogeneous and complex.
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Affiliation(s)
- Ian M McCullough
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, 48824, USA
| | - Kendra Spence Cheruvelil
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, 48824, USA
- Lyman Briggs College, Michigan State University, East Lansing, Michigan, 48824, USA
| | - Sarah M Collins
- Center for Limnology, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Patricia A Soranno
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, 48824, USA
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24
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Cheruvelil KS, Soranno PA. Data-Intensive Ecological Research Is Catalyzed by Open Science and Team Science. Bioscience 2018. [DOI: 10.1093/biosci/biy097] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Kendra Spence Cheruvelil
- Professor in Lyman Briggs College and the Department of Fisheries and Wildlife
- Conceptualization and writing of this article
| | - Patricia A Soranno
- Professor in the Department of Fisheries and Wildlife, at Michigan State University, in East Lansing
- Conceptualization and writing of this article
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25
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Soranno PA, Bacon LC, Beauchene M, Bednar KE, Bissell EG, Boudreau CK, Boyer MG, Bremigan MT, Carpenter SR, Carr JW, Cheruvelil KS, Christel ST, Claucherty M, Collins SM, Conroy JD, Downing JA, Dukett J, Fergus CE, Filstrup CT, Funk C, Gonzalez MJ, Green LT, Gries C, Halfman JD, Hamilton SK, Hanson PC, Henry EN, Herron EM, Hockings C, Jackson JR, Jacobson-Hedin K, Janus LL, Jones WW, Jones JR, Keson CM, King KBS, Kishbaugh SA, Lapierre JF, Lathrop B, Latimore JA, Lee Y, Lottig NR, Lynch JA, Matthews LJ, McDowell WH, Moore KEB, Neff BP, Nelson SJ, Oliver SK, Pace ML, Pierson DC, Poisson AC, Pollard AI, Post DM, Reyes PO, Rosenberry DO, Roy KM, Rudstam LG, Sarnelle O, Schuldt NJ, Scott CE, Skaff NK, Smith NJ, Spinelli NR, Stachelek JJ, Stanley EH, Stoddard JL, Stopyak SB, Stow CA, Tallant JM, Tan PN, Thorpe AP, Vanni MJ, Wagner T, Watkins G, Weathers KC, Webster KE, White JD, Wilmes MK, Yuan S. LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes. Gigascience 2018; 6:1-22. [PMID: 29053868 PMCID: PMC5721373 DOI: 10.1093/gigascience/gix101] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Accepted: 10/05/2017] [Indexed: 11/18/2022] Open
Abstract
Understanding the factors that affect water quality and the ecological services provided by freshwater ecosystems is an urgent global environmental issue. Predicting how water quality will respond to global changes not only requires water quality data, but also information about the ecological context of individual water bodies across broad spatial extents. Because lake water quality is usually sampled in limited geographic regions, often for limited time periods, assessing the environmental controls of water quality requires compilation of many data sets across broad regions and across time into an integrated database. LAGOS-NE accomplishes this goal for lakes in the northeastern-most 17 US states. LAGOS-NE contains data for 51 101 lakes and reservoirs larger than 4 ha in 17 lake-rich US states. The database includes 3 data modules for: lake location and physical characteristics for all lakes; ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes; and in situ measurements of lake water quality for a subset of the lakes from the past 3 decades for approximately 2600–12 000 lakes depending on the variable. The database contains approximately 150 000 measures of total phosphorus, 200 000 measures of chlorophyll, and 900 000 measures of Secchi depth. The water quality data were compiled from 87 lake water quality data sets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. This database is one of the largest and most comprehensive databases of its type because it includes both in situ measurements and ecological context data. Because ecological context can be used to study a variety of other questions about lakes, streams, and wetlands, this database can also be used as the foundation for other studies of freshwaters at broad spatial and ecological scales.
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Affiliation(s)
- Patricia A Soranno
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Linda C Bacon
- Department of Environmental Protection, State of Maine, Augusta, ME 04330, USA
| | - Michael Beauchene
- Department of Energy and Environmental Protection, State of Connecticut, Hartford, CT 06106, USA
| | - Karen E Bednar
- Water Resources Program, Lac du Flambeau Tribal Natural Resources, Lac du Flambeau, WI, USA
| | - Edward G Bissell
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Claire K Boudreau
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Marvin G Boyer
- Environmental Planning, US Army Corps of Engineers, Kansas City, MO 64106, USA
| | - Mary T Bremigan
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Stephen R Carpenter
- Center for Limnology, University of Wisconsin Madison, Madison, WI 53706 USA
| | - Jamie W Carr
- Office of Watershed Management, Massachusetts Department of Conservation and Recreation, West Boylston, MA 10583, USA
| | - Kendra S Cheruvelil
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Samuel T Christel
- Center for Limnology, University of Wisconsin Madison, Madison, WI 53706 USA
| | - Matt Claucherty
- Watershed Protection, Tipp of the Mitt Watershed Council, Petoskey, MI 49770, USA
| | - Sarah M Collins
- Center for Limnology, University of Wisconsin Madison, Madison, WI 53706 USA
| | - Joseph D Conroy
- Division of Wildlife, Inland Fisheries Research Unit, Ohio Department of Natural Resources, Hebron, OH 43025, USA
| | - John A Downing
- Large Lakes Observatory, University of Minnesota, Duluth, MN 55812 USA
| | - Jed Dukett
- Adirondack Lake Survey Corporation, Ray Brook, NY 12977 USA
| | - C Emi Fergus
- National Research Council, US Environmental Protection Agency, Corvallis, OR 97333, USA
| | | | - Clara Funk
- Office of Air and Radiation, US Environmental Protection Agency, Washington, DC 20460, USA
| | | | - Linda T Green
- Natural Resource Science, University of Rhode Island, Kingston, RI 02892 USA
| | - Corinna Gries
- Center for Limnology, University of Wisconsin Madison, Madison, WI 53706 USA
| | - John D Halfman
- Geoscience, Hobart & William Smith Colleges, Geneva, NY 14456 USA
| | - Stephen K Hamilton
- Kellogg Biological Station, Michigan State University, Hickory Corners, MI 49060, USA
| | - Paul C Hanson
- Center for Limnology, University of Wisconsin Madison, Madison, WI 53706 USA
| | - Emily N Henry
- Outreach and Engagement, Oregon State University, Corvallis, OR 97331, USA
| | | | - Celeste Hockings
- Natural Resource Department, Lac du Flambeau Band of Lake Superior Chippewa Indians, Lac du Flambeau, WI 54538, USA
| | - James R Jackson
- Department of Natural Resources, Cornell University, Bridgeport, NY, USA
| | | | - Lorraine L Janus
- Bureau of Water Supply, New York City Department of Environmental Protection, Valhalla, NY 10560, USA
| | - William W Jones
- School of Public and Environmental Affairs, Indiana University, Bloomington, IN 47408, USA
| | - John R Jones
- School of Natural Resources, University of Missouri, Columbia, MO, USA
| | - Caroline M Keson
- Natural Resource Department, Little Traverse Bay Bands of Odawa Indians, Harbor Springs, MI 49740, USA
| | - Katelyn B S King
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Scott A Kishbaugh
- Division of Water, New York State Department of Environmental Conservation, Albany, NY 12233, USA
| | - Jean-Francois Lapierre
- Department of Biological Science, University of Montreal, Montreal Quebec, Canada, H3C 3J7
| | - Barbara Lathrop
- Pennsylvania Department of Environmental Protection, State of Pennsylvania, Harrisburg, PA 17101 USA
| | - Jo A Latimore
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Yuehlin Lee
- Office of Watershed Management, Massachusetts Department of Conservation and Recreation, Belchertown, MA 01007, USA
| | - Noah R Lottig
- Trout Lake Research Station, University of Wisconsin, Boulder Junction, WI 54512, USA
| | - Jason A Lynch
- Office of Air and Radiation, US Environmental Protection Agency, Washington, DC 20460, USA
| | - Leslie J Matthews
- Lakes and Ponds Program, Vermont Department of Environmental Conservation, Montpelier, VT 05620, USA
| | - William H McDowell
- Natural Resources and the Environment, University of New Hampshire, Durham, NH 03824, USA
| | - Karen E B Moore
- Water Quality Science and Research, New York City Department of Environmental Protection, Kingston, NY 12401, USA
| | - Brian P Neff
- National Research Program, USGS, Denver CO 80225, USA
| | - Sarah J Nelson
- School of Forest Resources, University of Maine, Orono, ME, USA
| | - Samantha K Oliver
- Center for Limnology, University of Wisconsin Madison, Madison, WI 53706 USA
| | - Michael L Pace
- Department of Environmental Science, University of Virginia, Charlottesville, VA 22904, USA
| | - Donald C Pierson
- Department of Ecology and Genetics, Uppsala University, Uppsala, Sweden
| | - Autumn C Poisson
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | | | - David M Post
- Ecology and Evolutionary Biology, Yale University, Connecticut 06511, USA
| | - Paul O Reyes
- Office of Watershed Management, Massachusetts Department of Conservation and Recreation, Belchertown, MA 01007, USA
| | | | - Karen M Roy
- Division of Air Resources, New York State Department of Environmental Conservation, Ray Brook, NY 12977, USA
| | - Lars G Rudstam
- Department of Natural Resources, Cornell University, Ithaca, NY 14850, USA
| | - Orlando Sarnelle
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Nancy J Schuldt
- Environmental Program, Fond du Lac Band of Lake Superior Chippewa Indians, Cloquet, MN 55720, USA
| | | | - Nicholas K Skaff
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Nicole J Smith
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Nick R Spinelli
- Watershed Management, Lake Wallenpaupack Watershed Management District, Hawley, PA, USA
| | - Joseph J Stachelek
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | - Emily H Stanley
- Center for Limnology, University of Wisconsin Madison, Madison, WI 53706 USA
| | - John L Stoddard
- Western Ecology Division, Office of Research and Development, US EPA, Corvallis, OR 97333, USA
| | | | - Craig A Stow
- Great Lakes Environmental Research Lab, NOAA, Ann Arbor, MI 47176, USA
| | - Jason M Tallant
- Biological Station, University of Michigan, Pellston, MI 49769, USA
| | - Pang-Ning Tan
- Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
| | - Anthony P Thorpe
- School of Natural Resources, University of Missouri, Columbia, MO, USA
| | - Michael J Vanni
- Department of Zoology, Miami University, Oxford, OH 45056 USA
| | - Tyler Wagner
- Pennsylvania Cooperative Fish and Wildlife Research Unit, USGS, 402 Forest Resources Building, University Park, PA 16802, USA
| | - Gretchen Watkins
- Water Resources Program, Lac du Flambeau Tribal Natural Resources, Lac du Flambeau, WI, USA
| | | | | | - Jeffrey D White
- Biology Department, Framingham State University, Framingham, MA 01702, USA
| | - Marcy K Wilmes
- Department of Environmental Quality, State of Michigan, Lansing, MI 48909, USA
| | - Shuai Yuan
- Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
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Mantzouki E, Ibelings BW. The Principle and Value of the European Multi Lake Survey. ACTA ACUST UNITED AC 2018. [DOI: 10.1002/lob.10259] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Evanthia Mantzouki
- Department F.-A. Forel for Environmental and Aquatic Sciences, University of Geneva, Geneva, Switzerland
| | - Bas W. Ibelings
- Department F.-A. Forel for Environmental and Aquatic Sciences, University of Geneva, Geneva, Switzerland
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Peters K, Worrich A, Weinhold A, Alka O, Balcke G, Birkemeyer C, Bruelheide H, Calf OW, Dietz S, Dührkop K, Gaquerel E, Heinig U, Kücklich M, Macel M, Müller C, Poeschl Y, Pohnert G, Ristok C, Rodríguez VM, Ruttkies C, Schuman M, Schweiger R, Shahaf N, Steinbeck C, Tortosa M, Treutler H, Ueberschaar N, Velasco P, Weiß BM, Widdig A, Neumann S, Dam NMV. Current Challenges in Plant Eco-Metabolomics. Int J Mol Sci 2018; 19:E1385. [PMID: 29734799 PMCID: PMC5983679 DOI: 10.3390/ijms19051385] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Revised: 04/24/2018] [Accepted: 04/25/2018] [Indexed: 12/22/2022] Open
Abstract
The relatively new research discipline of Eco-Metabolomics is the application of metabolomics techniques to ecology with the aim to characterise biochemical interactions of organisms across different spatial and temporal scales. Metabolomics is an untargeted biochemical approach to measure many thousands of metabolites in different species, including plants and animals. Changes in metabolite concentrations can provide mechanistic evidence for biochemical processes that are relevant at ecological scales. These include physiological, phenotypic and morphological responses of plants and communities to environmental changes and also interactions with other organisms. Traditionally, research in biochemistry and ecology comes from two different directions and is performed at distinct spatiotemporal scales. Biochemical studies most often focus on intrinsic processes in individuals at physiological and cellular scales. Generally, they take a bottom-up approach scaling up cellular processes from spatiotemporally fine to coarser scales. Ecological studies usually focus on extrinsic processes acting upon organisms at population and community scales and typically study top-down and bottom-up processes in combination. Eco-Metabolomics is a transdisciplinary research discipline that links biochemistry and ecology and connects the distinct spatiotemporal scales. In this review, we focus on approaches to study chemical and biochemical interactions of plants at various ecological levels, mainly plant⁻organismal interactions, and discuss related examples from other domains. We present recent developments and highlight advancements in Eco-Metabolomics over the last decade from various angles. We further address the five key challenges: (1) complex experimental designs and large variation of metabolite profiles; (2) feature extraction; (3) metabolite identification; (4) statistical analyses; and (5) bioinformatics software tools and workflows. The presented solutions to these challenges will advance connecting the distinct spatiotemporal scales and bridging biochemistry and ecology.
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Affiliation(s)
- Kristian Peters
- Leibniz Institute of Plant Biochemistry, Stress and Developmental Biology, Weinberg 3, 06120 Halle (Saale), Germany.
| | - Anja Worrich
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany.
- Institute of Biodiversity, Friedrich Schiller University Jena, Dornburger-Str. 159, 07743 Jena, Germany.
- UFZ-Helmholtz-Centre for Environmental Research, Department Environmental Microbiology, Permoserstraße 15, 04318 Leipzig, Germany.
| | - Alexander Weinhold
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany.
- Institute of Biodiversity, Friedrich Schiller University Jena, Dornburger-Str. 159, 07743 Jena, Germany.
| | - Oliver Alka
- Applied Bioinformatics Group, Center for Bioinformatics, University of Tübingen, Sand 14, 72076 Tübingen, Germany.
| | - Gerd Balcke
- Leibniz Institute of Plant Biochemistry, Cell and Metabolic Biology, Weinberg 3, 06120 Halle (Saale), Germany.
| | - Claudia Birkemeyer
- Institute of Analytical Chemistry, University of Leipzig, Linnéstr. 3, 04103 Leipzig, Germany.
| | - Helge Bruelheide
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany.
- Institute of Biology/Geobotany and Botanical Garden, Martin Luther University Halle-Wittenberg, Am Kirchtor 1, 06108 Halle (Saale), Germany.
| | - Onno W Calf
- Molecular Interaction Ecology, Institute for Water and Wetland Research (IWWR), Radboud University, Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands.
| | - Sophie Dietz
- Leibniz Institute of Plant Biochemistry, Stress and Developmental Biology, Weinberg 3, 06120 Halle (Saale), Germany.
| | - Kai Dührkop
- Department of Bioinformatics, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany.
| | - Emmanuel Gaquerel
- Centre for Organismal Studies, Heidelberg University, Im Neuenheimer Feld 360, 69120 Heidelberg, Germany.
| | - Uwe Heinig
- Weizmann Institute of Science, Faculty of Biochemistry, Department of Plant Sciences, 234 Herzl St., P.O. Box 26, Rehovot 7610001, Israel.
| | - Marlen Kücklich
- Institute of Biology, University of Leipzig, Talstraße 33, 04109 Leipzig, Germany.
| | - Mirka Macel
- Molecular Interaction Ecology, Institute for Water and Wetland Research (IWWR), Radboud University, Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands.
| | - Caroline Müller
- Chemical Ecology, Bielefeld University, Universitätsstr. 25, 33615 Bielefeld, Germany.
| | - Yvonne Poeschl
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany.
- Institute of Informatics, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, 06120 Halle (Saale), Germany.
| | - Georg Pohnert
- Institute of Inorganic and Analytical Chemistry, Friedrich Schiller University Jena, Lessingstr. 8, 07743 Jena, Germany.
| | - Christian Ristok
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany.
| | - Victor Manuel Rodríguez
- Group of Genetics, Breeding and Biochemistry of Brassica, Misión Biológica de Galicia (CSIC), Apartado 28, 36080 Pontevedra, Spain.
| | - Christoph Ruttkies
- Leibniz Institute of Plant Biochemistry, Stress and Developmental Biology, Weinberg 3, 06120 Halle (Saale), Germany.
| | - Meredith Schuman
- Department of Molecular Ecology, Max Planck Institute for Chemical Ecology, Hans-Knöll-Straße 8, 07745 Jena, Germany.
| | - Rabea Schweiger
- Chemical Ecology, Bielefeld University, Universitätsstr. 25, 33615 Bielefeld, Germany.
| | - Nir Shahaf
- Weizmann Institute of Science, Faculty of Biochemistry, Department of Plant Sciences, 234 Herzl St., P.O. Box 26, Rehovot 7610001, Israel.
| | - Christoph Steinbeck
- Institute of Inorganic and Analytical Chemistry, Friedrich Schiller University Jena, Lessingstr. 8, 07743 Jena, Germany.
| | - Maria Tortosa
- Group of Genetics, Breeding and Biochemistry of Brassica, Misión Biológica de Galicia (CSIC), Apartado 28, 36080 Pontevedra, Spain.
| | - Hendrik Treutler
- Leibniz Institute of Plant Biochemistry, Stress and Developmental Biology, Weinberg 3, 06120 Halle (Saale), Germany.
| | - Nico Ueberschaar
- Institute of Inorganic and Analytical Chemistry, Friedrich Schiller University Jena, Lessingstr. 8, 07743 Jena, Germany.
| | - Pablo Velasco
- Group of Genetics, Breeding and Biochemistry of Brassica, Misión Biológica de Galicia (CSIC), Apartado 28, 36080 Pontevedra, Spain.
| | - Brigitte M Weiß
- Institute of Biology, University of Leipzig, Talstraße 33, 04109 Leipzig, Germany.
| | - Anja Widdig
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany.
- Institute of Biology, University of Leipzig, Talstraße 33, 04109 Leipzig, Germany.
- Research Group of Primate Kin Selection, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany.
| | - Steffen Neumann
- Leibniz Institute of Plant Biochemistry, Stress and Developmental Biology, Weinberg 3, 06120 Halle (Saale), Germany.
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany.
| | - Nicole M van Dam
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany.
- Institute of Biodiversity, Friedrich Schiller University Jena, Dornburger-Str. 159, 07743 Jena, Germany.
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Cobourn KM, Carey CC, Boyle KJ, Duffy C, Dugan HA, Farrell KJ, Fitchett L, Hanson PC, Hart JA, Henson VR, Hetherington AL, Kemanian AR, Rudstam LG, Shu L, Soranno PA, Sorice MG, Stachelek J, Ward NK, Weathers KC, Weng W, Zhang Y. From concept to practice to policy: modeling coupled natural and human systems in lake catchments. Ecosphere 2018. [DOI: 10.1002/ecs2.2209] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- Kelly M. Cobourn
- Department of Forest Resources and Environmental Conservation Virginia Tech 310 W Campus Dr. Blacksburg Virginia 24061 USA
| | - Cayelan C. Carey
- Department of Biological Sciences Virginia Tech 926 W Campus Dr. Blacksburg Virginia 24061 USA
| | - Kevin J. Boyle
- Department of Agricultural and Applied Economics Virginia Tech 250 Drillfield Dr. Blacksburg Virginia 24061 USA
| | - Christopher Duffy
- Department of Civil and Environmental Engineering The Pennsylvania State University 231G Sackett Bldg. University Park Pennsylvania 16802 USA
| | - Hilary A. Dugan
- Center for Limnology University of Wisconsin‐Madison 680 N Park St. Madison Wisconsin 53706 USA
| | - Kaitlin J. Farrell
- Department of Biological Sciences Virginia Tech 926 W Campus Dr. Blacksburg Virginia 24061 USA
| | - Leah Fitchett
- Department of Forest Resources and Environmental Conservation Virginia Tech 310 W Campus Dr. Blacksburg Virginia 24061 USA
| | - Paul C. Hanson
- Center for Limnology University of Wisconsin‐Madison 680 N Park St. Madison Wisconsin 53706 USA
| | - Julia A. Hart
- College of the Environment University of Washington 1492 NE Boat St. Seattle Washington 98105 USA
| | - Virginia Reilly Henson
- Department of Forest Resources and Environmental Conservation Virginia Tech 310 W Campus Dr. Blacksburg Virginia 24061 USA
| | - Amy L. Hetherington
- Department of Forest Resources and Environmental Conservation Virginia Tech 310 W Campus Dr. Blacksburg Virginia 24061 USA
- Department of Biological Sciences Virginia Tech 926 W Campus Dr. Blacksburg Virginia 24061 USA
| | - Armen R. Kemanian
- Department of Plant Science The Pennsylvania State University 247 Agricultural Sciences and Industries Bldg. University Park Pennsylvania 16802 USA
| | - Lars G. Rudstam
- Department of Natural Resources Cornell University 211A Fernow Hall Ithaca New York 54732 USA
| | - Lele Shu
- Department of Civil and Environmental Engineering The Pennsylvania State University 231G Sackett Bldg. University Park Pennsylvania 16802 USA
| | - Patricia A. Soranno
- Department of Fisheries and Wildlife Michigan State University 480 Wilson Rd. East Lansing Michigan 48824 USA
| | - Michael G. Sorice
- Department of Forest Resources and Environmental Conservation Virginia Tech 310 W Campus Dr. Blacksburg Virginia 24061 USA
| | - Jemma Stachelek
- Department of Fisheries and Wildlife Michigan State University 480 Wilson Rd. East Lansing Michigan 48824 USA
| | - Nicole K. Ward
- Department of Biological Sciences Virginia Tech 926 W Campus Dr. Blacksburg Virginia 24061 USA
| | - Kathleen C. Weathers
- Cary Institute of Ecosystem Studies 2801 Sharon Tpke. Millbrook New York 12545 USA
| | - Weizhe Weng
- Department of Agricultural and Applied Economics Virginia Tech 250 Drillfield Dr. Blacksburg Virginia 24061 USA
| | - Yu Zhang
- Nicholas School of the Environment Duke University 9 Circuit Dr. Durham North Carolina 27708 USA
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Stow CA, Webster KE, Wagner T, Lottig N, Soranno PA, Cha Y. Small values in big data: The continuing need for appropriate metadata. ECOL INFORM 2018. [DOI: 10.1016/j.ecoinf.2018.03.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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Pollard AI, Hampton SE, Leech DM. The Promise and Potential of Continental-Scale Limnology Using the U.S. Environmental Protection Agency's National Lakes Assessment. ACTA ACUST UNITED AC 2018. [DOI: 10.1002/lob.10238] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
| | - Stephanie E. Hampton
- Center for Environmental Research, Education and Outreach; Washington State University; Pullman WA
| | - Dina M. Leech
- Department of Biological and Environmental Sciences; Longwood University; Farmville VA
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31
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James SA, Soltis PS, Belbin L, Chapman AD, Nelson G, Paul DL, Collins M. Herbarium data: Global biodiversity and societal botanical needs for novel research. APPLICATIONS IN PLANT SCIENCES 2018; 6:e1024. [PMID: 29732255 PMCID: PMC5851569 DOI: 10.1002/aps3.1024] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 12/30/2017] [Indexed: 05/11/2023]
Abstract
Building on centuries of research based on herbarium specimens gathered through time and around the globe, a new era of discovery, synthesis, and prediction using digitized collections data has begun. This paper provides an overview of how aggregated, open access botanical and associated biological, environmental, and ecological data sets, from genes to the ecosystem, can be used to document the impacts of global change on communities, organisms, and society; predict future impacts; and help to drive the remediation of change. Advocacy for botanical collections and their expansion is needed, including ongoing digitization and online publishing. The addition of non-traditional digitized data fields, user annotation capability, and born-digital field data collection enables the rapid access of rich, digitally available data sets for research, education, informed decision-making, and other scholarly and creative activities. Researchers are receiving enormous benefits from data aggregators including the Global Biodiversity Information Facility (GBIF), Integrated Digitized Biocollections (iDigBio), the Atlas of Living Australia (ALA), and the Biodiversity Heritage Library (BHL), but effective collaboration around data infrastructures is needed when working with large and disparate data sets. Tools for data discovery, visualization, analysis, and skills training are increasingly important for inspiring novel research that improves the intrinsic value of physical and digital botanical collections.
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Affiliation(s)
- Shelley A. James
- National Herbarium of New South WalesRoyal Botanic Gardens and Domain TrustMrs Macquaries RoadSydneyNew South Wales2000Australia
| | - Pamela S. Soltis
- Florida Museum of Natural HistoryUniversity of FloridaGainesvilleFlorida32611USA
| | - Lee Belbin
- Atlas of Living AustraliaCSIROClunies Ross StreetActonAustralia Capital Territory2601Australia
| | - Arthur D. Chapman
- Australian Biodiversity Information ServicesBallanVictoria3342Australia
| | - Gil Nelson
- iDigBioFlorida State UniversityTallahasseeFlorida32306USA
| | | | - Matthew Collins
- Advanced Computing and Information SystemsUniversity of FloridaGainesvilleFlorida32611USA
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32
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The Global Lake Ecological Observatory Network. ECOL INFORM 2018. [DOI: 10.1007/978-3-319-59928-1_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Lottig NR, Tan P, Wagner T, Cheruvelil KS, Soranno PA, Stanley EH, Scott CE, Stow CA, Yuan S. Macroscale patterns of synchrony identify complex relationships among spatial and temporal ecosystem drivers. Ecosphere 2017. [DOI: 10.1002/ecs2.2024] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Affiliation(s)
- Noah R. Lottig
- University of Wisconsin Center for Limnology Trout Lake Station, 3110 Trout Lake Station Dr. Boulder Junction Wisconsin 54531 USA
| | - Pang‐Ning Tan
- Department of Computer Science & Engineering Michigan State University 428 South Shaw Lane, Room 3115 East Lansing Michigan 48824 USA
| | - Tyler Wagner
- U.S. Geological Survey Pennsylvania Cooperative Fish and Wildlife Research Unit The Pennsylvania State University 420 Forest Resources Building University Park Pennsylvania 16802 USA
| | - Kendra Spence Cheruvelil
- Department of Fisheries and Wildlife & Lyman Briggs College Michigan State University Natural Resources Building, 480 Wilson Road, Room 334D East Lansing Michigan 48824 USA
| | - Patricia A. Soranno
- Department of Fisheries and Wildlife Michigan State University Natural Resources Building, 480 Wilson Road, Room 334D East Lansing Michigan 48824 USA
| | - Emily H. Stanley
- University of Wisconsin Center for Limnology 680 North Park Street Madison Wisconsin 53706 USA
| | - Caren E. Scott
- Department of Fisheries and Wildlife Michigan State University Natural Resources Building, 480 Wilson Road, Room 334D East Lansing Michigan 48824 USA
| | - Craig A. Stow
- NOAA Great Lakes Environmental Research Laboratory 4840 South State Road Ann Arbor Michigan 48108 USA
| | - Shuai Yuan
- Department of Computer Science & Engineering Michigan State University 428 South Shaw Lane, Room 3115 East Lansing Michigan 48824 USA
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Oliver SK, Collins SM, Soranno PA, Wagner T, Stanley EH, Jones JR, Stow CA, Lottig NR. Unexpected stasis in a changing world: Lake nutrient and chlorophyll trends since 1990. GLOBAL CHANGE BIOLOGY 2017; 23:5455-5467. [PMID: 28834575 DOI: 10.1111/gcb.13810] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Accepted: 05/31/2017] [Indexed: 06/07/2023]
Abstract
The United States (U.S.) has faced major environmental changes in recent decades, including agricultural intensification and urban expansion, as well as changes in atmospheric deposition and climate-all of which may influence eutrophication of freshwaters. However, it is unclear whether or how water quality in lakes across diverse ecological settings has responded to environmental change. We quantified water quality trends in 2913 lakes using nutrient and chlorophyll (Chl) observations from the Lake Multi-Scaled Geospatial and Temporal Database of the Northeast U.S. (LAGOS-NE), a collection of preexisting lake data mostly from state agencies. LAGOS-NE was used to quantify whether lake water quality has changed from 1990 to 2013, and whether lake-specific or regional geophysical factors were related to the observed changes. We modeled change through time using hierarchical linear models for total nitrogen (TN), total phosphorus (TP), stoichiometry (TN:TP), and Chl. Both the slopes (percent change per year) and intercepts (value in 1990) were allowed to vary by lake and region. Across all lakes, TN declined at a rate of 1.1% year-1 , while TP, TN:TP, and Chl did not change. A minority (7%-16%) of individual lakes had changing nutrients, stoichiometry, or Chl. Of those lakes that changed, we found differences in the geospatial variables that were most related to the observed change in the response variables. For example, TN and TN:TP trends were related to region-level drivers associated with atmospheric deposition of N; TP trends were related to both lake and region-level drivers associated with climate and land use; and Chl trends were found in regions with high air temperature at the beginning of the study period. We conclude that despite large environmental change and management efforts over recent decades, water quality of lakes in the Midwest and Northeast U.S. has not overwhelmingly degraded or improved.
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Affiliation(s)
- Samantha K Oliver
- Center for Limnology, University of Wisconsin-Madison, Madison, WI, USA
| | - Sarah M Collins
- Center for Limnology, University of Wisconsin-Madison, Madison, WI, USA
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
| | - Patricia A Soranno
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
| | - Tyler Wagner
- U.S. Geological Survey, Pennsylvania Cooperative Fish and Wildlife Research Unit, The Pennsylvania State University, University Park, PA, USA
| | - Emily H Stanley
- Center for Limnology, University of Wisconsin-Madison, Madison, WI, USA
| | - John R Jones
- Department of Fisheries and Wildlife Sciences, University of Missouri, Columbia, MO, USA
| | - Craig A Stow
- NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, MI, USA
| | - Noah R Lottig
- Center for Limnology, University of Wisconsin-Madison, Madison, WI, USA
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35
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Durden JM, Luo JY, Alexander H, Flanagan AM, Grossmann L. Integrating “Big Data” into Aquatic Ecology: Challenges and Opportunities. ACTA ACUST UNITED AC 2017. [DOI: 10.1002/lob.10213] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Skaff NK, Armstrong PM, Andreadis TG, Cheruvelil KS. Wetland characteristics linked to broad-scale patterns in Culiseta melanura abundance and eastern equine encephalitis virus infection. Parasit Vectors 2017; 10:501. [PMID: 29047412 PMCID: PMC5648514 DOI: 10.1186/s13071-017-2482-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Accepted: 10/13/2017] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Eastern equine encephalitis virus (EEEV) is an expanding mosquito-borne threat to humans and domestic animal populations in the northeastern United States. Outbreaks of EEEV are challenging to predict due to spatial and temporal uncertainty in the abundance and viral infection of Cs. melanura, the principal enzootic vector. EEEV activity may be closely linked to wetlands because they provide essential habitat for mosquito vectors and avian reservoir hosts. However, wetlands are not homogeneous and can vary by vegetation, connectivity, size, and inundation patterns. Wetlands may also have different effects on EEEV transmission depending on the assessed spatial scale. We investigated associations between wetland characteristics and Cs. melanura abundance and infection with EEEV at multiple spatial scales in Connecticut, USA. RESULTS Our findings indicate that wetland vegetative characteristics have strong associations with Cs. melanura abundance. Deciduous and evergreen forested wetlands were associated with higher Cs. melanura abundance, likely because these wetlands provide suitable subterranean habitat for Cs. melanura development. In contrast, Cs. melanura abundance was negatively associated with emergent and scrub/shrub wetlands, and wetland connectivity to streams. These relationships were generally strongest at broad spatial scales. Additionally, the relationships between wetland characteristics and EEEV infection in Cs. melanura were generally weak. However, Cs. melanura abundance was strongly associated with EEEV infection, suggesting that wetland-associated changes in abundance may be indirectly linked to EEEV infection in Cs. melanura. Finally, we found that wet hydrological conditions during the transmission season and during the fall/winter preceding the transmission season were associated with higher Cs. melanura abundance and EEEV infection, indicating that wet conditions are favorable for EEEV transmission. CONCLUSIONS These results expand the broad-scale understanding of the effects of wetlands on EEEV transmission and help to reduce the spatial and temporal uncertainty associated with EEEV outbreaks.
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Affiliation(s)
- Nicholas K Skaff
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA. .,Ecology, Evolutionary Biology & Behavior Program, Michigan State University, East Lansing, MI, USA.
| | - Philip M Armstrong
- Department of Environmental Sciences, The Connecticut Agricultural Experiment Station, New Haven, CT, USA
| | - Theodore G Andreadis
- Department of Environmental Sciences, The Connecticut Agricultural Experiment Station, New Haven, CT, USA
| | - Kendra S Cheruvelil
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA.,Lyman Briggs College, Michigan State University, East Lansing, MI, USA
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Abstract
Metrics describing the shape and size of lakes, known as lake morphometry metrics, are important for any limnological study. In cases where a lake has long been the subject of study these data are often already collected and are openly available. Many other lakes have these data collected, but access is challenging as it is often stored on individual computers (or worse, in filing cabinets) and is available only to the primary investigators. The vast majority of lakes fall into a third category in which the data are not available. This makes broad scale modelling of lake ecology a challenge as some of the key information about in-lake processes are unavailable. While this valuable in situ information may be difficult to obtain, several national datasets exist that may be used to model and estimate lake morphometry. In particular, digital elevation models and hydrography have been shown to be predictive of several lake morphometry metrics. The R package lakemorpho has been developed to utilize these data and estimate the following morphometry metrics: surface area, shoreline length, major axis length, minor axis length, major and minor axis length ratio, shoreline development, maximum depth, mean depth, volume, maximum lake length, mean lake width, maximum lake width, and fetch. In this software tool article we describe the motivation behind developing lakemorpho, discuss the implementation in R, and describe the use of lakemorpho with an example of a typical use case.
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Affiliation(s)
- Jeffrey Hollister
- US Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Atlantic Ecology Division, Narragansett, RI, USA
| | - Joseph Stachelek
- Michigan State University, Department of Fisheries and Wildlife, Natural Resources Building, East Lansing, MI, USA
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38
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The freshwater landscape: lake, wetland, and stream abundance and connectivity at macroscales. Ecosphere 2017. [DOI: 10.1002/ecs2.1911] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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39
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Collins SM, Oliver SK, Lapierre JF, Stanley EH, Jones JR, Wagner T, Soranno PA. Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub-continental scales. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2017; 27:1529-1540. [PMID: 28370707 DOI: 10.1002/eap.1545] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Revised: 03/01/2017] [Accepted: 03/08/2017] [Indexed: 06/07/2023]
Abstract
Production in many ecosystems is co-limited by multiple elements. While a known suite of drivers associated with nutrient sources, nutrient transport, and internal processing controls concentrations of phosphorus (P) and nitrogen (N) in lakes, much less is known about whether the drivers of single nutrient concentrations can also explain spatial or temporal variation in lake N:P stoichiometry. Predicting stoichiometry might be more complex than predicting concentrations of individual elements because some drivers have similar relationships with N and P, leading to a weak relationship with their ratio. Further, the dominant controls on elemental concentrations likely vary across regions, resulting in context dependent relationships between drivers, lake nutrients and their ratios. Here, we examine whether known drivers of N and P concentrations can explain variation in N:P stoichiometry, and whether explaining variation in stoichiometry differs across regions. We examined drivers of N:P in ~2,700 lakes at a sub-continental scale and two large regions nested within the sub-continental study area that have contrasting ecological context, including differences in the dominant type of land cover (agriculture vs. forest). At the sub-continental scale, lake nutrient concentrations were correlated with nutrient loading and lake internal processing, but stoichiometry was only weakly correlated to drivers of lake nutrients. At the regional scale, drivers that explained variation in nutrients and stoichiometry differed between regions. In the Midwestern U.S. region, dominated by agricultural land use, lake depth and the percentage of row crop agriculture were strong predictors of stoichiometry because only phosphorus was related to lake depth and only nitrogen was related to the percentage of row crop agriculture. In contrast, all drivers were related to N and P in similar ways in the Northeastern U.S. region, leading to weak relationships between drivers and stoichiometry. Our results suggest ecological context mediates controls on lake nutrients and stoichiometry. Predicting stoichiometry was generally more difficult than predicting nutrient concentrations, but human activity may decouple N and P, leading to better prediction of N:P stoichiometry in regions with high anthropogenic activity.
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Affiliation(s)
- Sarah M Collins
- Department of Fisheries and Wildlife, Michigan State University, 13 Natural Resources, East Lansing, Michigan, 48824, USA
- Center for Limnology, University of Wisconsin, 680 North Park Street, Madison, Wisconsin, 53706, USA
| | - Samantha K Oliver
- Center for Limnology, University of Wisconsin, 680 North Park Street, Madison, Wisconsin, 53706, USA
| | - Jean-Francois Lapierre
- Département de Sciences Biologiques, Université de Montreal, Pavillon Marie-Victorin, CP 6128, succursale Centre-ville, Montréal, Quebec, H3C 3J7, Canada
| | - Emily H Stanley
- Center for Limnology, University of Wisconsin, 680 North Park Street, Madison, Wisconsin, 53706, USA
| | - John R Jones
- School of Natural Resources, University of Missouri, 302 Anheuser-Busch Natural Resources Building, Columbia, Missouri, 65211, USA
| | - Tyler Wagner
- U.S. Geological Survey, Pennsylvania Cooperative Fish and Wildlife Unit, The Pennsylvania State University, 402 Forest Resources Building, University Park, Pennsylvania, 16802, USA
| | - Patricia A Soranno
- Department of Fisheries and Wildlife, Michigan State University, 13 Natural Resources, East Lansing, Michigan, 48824, USA
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40
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Williams J, Labou SG. A database of georeferenced nutrient chemistry data for mountain lakes of the Western United States. Sci Data 2017; 4:170069. [PMID: 28509907 PMCID: PMC5479644 DOI: 10.1038/sdata.2017.69] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Accepted: 04/03/2017] [Indexed: 11/09/2022] Open
Abstract
Human activities have increased atmospheric nitrogen and phosphorus deposition rates relative to pre-industrial background. In the Western U.S., anthropogenic nutrient deposition has increased nutrient concentrations and stimulated algal growth in at least some remote mountain lakes. The Georeferenced Lake Nutrient Chemistry (GLNC) Database was constructed to create a spatially-extensive lake chemistry database needed to assess atmospheric nutrient deposition effects on Western U.S. mountain lakes. The database includes nitrogen and phosphorus water chemistry data spanning 1964–2015, with 148,336 chemistry results from 51,048 samples collected across 3,602 lakes in the Western U.S. Data were obtained from public databases, government agencies, scientific literature, and researchers, and were formatted into a consistent table structure. All data are georeferenced to a modified version of the National Hydrography Dataset Plus version 2. The database is transparent and reproducible; R code and input files used to format data are provided in an appendix. The database will likely be useful to those assessing spatial patterns of lake nutrient chemistry associated with atmospheric deposition or other environmental stressors.
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Affiliation(s)
- Jason Williams
- Washington State University, Department of Civil &Environmental Engineering, Pullman, Washington 99164, USA
| | - Stephanie G Labou
- Washington State University, Center for Environmental Research, Education, and Outreach (CEREO), PACCAR, Pullman, Washington 99164, USA
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41
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Hampton SE, Jones MB, Wasser LA, Schildhauer MP, Supp SR, Brun J, Hernandez RR, Boettiger C, Collins SL, Gross LJ, Fernández DS, Budden A, White EP, Teal TK, Labou SG, Aukema JE. Skills and Knowledge for Data-Intensive Environmental Research. Bioscience 2017; 67:546-557. [PMID: 28584342 PMCID: PMC5451289 DOI: 10.1093/biosci/bix025] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap.
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Affiliation(s)
- Stephanie E Hampton
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Matthew B Jones
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Leah A Wasser
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Mark P Schildhauer
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Sarah R Supp
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Julien Brun
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Rebecca R Hernandez
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Carl Boettiger
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Scott L Collins
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Louis J Gross
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Denny S Fernández
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Amber Budden
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Ethan P White
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Tracy K Teal
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Stephanie G Labou
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
| | - Juliann E Aukema
- Stephanie E. Hampton is affiliated with the Center for Environmental Research, Education and Outreach at Washington State University, in Pullman. Matthew B. Jones is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Leah A. Wasser is affiliated with EarthLab at the University of Colorado, in Boulder. Mark P. Schildhauer is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Sarah R. Supp is affiliated with the University of Maine's School of Biology and Ecology, in Orono. Julien Brun is with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara. Rebecca R. Hernandez is affiliated with the Land, Air, and Water Resources Department at the University of California, Davis; with the Energy and Resources Group at the University of California, Berkeley; and with the Climate and Carbon Science Program at the Lawrence Berkeley National Lab, in Berkeley, California. Carl Boettiger is affiliated with the Department of Environmental Science, Policy, and Management at the University of California, Berkeley. Scott L. Collins is with the Department of Biology at the University of New Mexico, in Albuquerque. Louis J. Gross is affiliated with the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, in Knoxville. Denny S. Fernández is with the Department of Biology at the University of Puerto Rico at Humacao. Amber Budden is affiliated with DataONE at the University of New Mexico, in Albuquerque. Ethan P. White is with the Department of Wildlife Ecology and Conservation and The Informatics Institute at the University of Florida, in Gainesville. Tracy K. Teal is affiliated with Data Carpentry, in Davis, California. Stephanie G. Labou is with the Center for Environmental Research, Education and Outreach, at Washington State University, in Pullman. Juliann E. Aukema is affiliated with the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara
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Cheruvelil KS, Yuan S, Webster KE, Tan PN, Lapierre JF, Collins SM, Fergus CE, Scott CE, Henry EN, Soranno PA, Filstrup CT, Wagner T. Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method. Ecol Evol 2017; 7:3046-3058. [PMID: 28480004 PMCID: PMC5415510 DOI: 10.1002/ece3.2884] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2016] [Revised: 01/26/2017] [Accepted: 02/07/2017] [Indexed: 11/11/2022] Open
Abstract
Understanding broad‐scale ecological patterns and processes often involves accounting for regional‐scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question—How well do these regions capture regional‐scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000 km2); (2) identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft‐ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation—approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional scale. Our results demonstrate the usefulness of this method for creating customizable and reproducible regions for research and management applications.
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Affiliation(s)
- Kendra Spence Cheruvelil
- Department of Fisheries and Wildlife & Lyman Briggs College Michigan State University East Lansing MI USA
| | - Shuai Yuan
- Department of Computer Science & Engineering Michigan State University East Lansing MI USA
| | | | - Pang-Ning Tan
- Department of Computer Science & Engineering Michigan State University East Lansing MI USA
| | - Jean-François Lapierre
- Département de Sciences Biologiques Université de Montréal, Pavillon Marie-Victorin Montréal QC Canada
| | | | - C Emi Fergus
- Department of Fisheries and Wildlife Michigan State University East Lansing MI USA
| | - Caren E Scott
- National Ecological Observatory Network Boulder CO USA
| | - Emily Norton Henry
- Division of Outreach and Engagement Oregon State University Corvallis OR USA
| | - Patricia A Soranno
- Department of Fisheries and Wildlife Michigan State University East Lansing MI USA
| | - Christopher T Filstrup
- Large Lakes Observatory & Minnesota Sea Grant University of Minnesota Duluth Duluth MN USA
| | - Tyler Wagner
- U.S. Geological Survey Pennsylvania Cooperative Fish & Wildlife Research Unit Pennsylvania State University University Park PA USA
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Fergus CE, Finley AO, Soranno PA, Wagner T. Spatial Variation in Nutrient and Water Color Effects on Lake Chlorophyll at Macroscales. PLoS One 2016; 11:e0164592. [PMID: 27736962 PMCID: PMC5063324 DOI: 10.1371/journal.pone.0164592] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2016] [Accepted: 09/27/2016] [Indexed: 11/18/2022] Open
Abstract
The nutrient-water color paradigm is a framework to characterize lake trophic status by relating lake primary productivity to both nutrients and water color, the colored component of dissolved organic carbon. Total phosphorus (TP), a limiting nutrient, and water color, a strong light attenuator, influence lake chlorophyll a concentrations (CHL). But, these relationships have been shown in previous studies to be highly variable, which may be related to differences in lake and catchment geomorphology, the forms of nutrients and carbon entering the system, and lake community composition. Because many of these factors vary across space it is likely that lake nutrient and water color relationships with CHL exhibit spatial autocorrelation, such that lakes near one another have similar relationships compared to lakes further away. Including this spatial dependency in models may improve CHL predictions and clarify how well the nutrient-water color paradigm applies to lakes distributed across diverse landscape settings. However, few studies have explicitly examined spatial heterogeneity in the effects of TP and water color together on lake CHL. In this study, we examined spatial variation in TP and water color relationships with CHL in over 800 north temperate lakes using spatially-varying coefficient models (SVC), a robust statistical method that applies a Bayesian framework to explore space-varying and scale-dependent relationships. We found that TP and water color relationships were spatially autocorrelated and that allowing for these relationships to vary by individual lakes over space improved the model fit and predictive performance as compared to models that did not vary over space. The magnitudes of TP effects on CHL differed across lakes such that a 1 μg/L increase in TP resulted in increased CHL ranging from 2–24 μg/L across lake locations. Water color was not related to CHL for the majority of lakes, but there were some locations where water color had a positive effect such that a unit increase in water color resulted in a 2 μg/L increase in CHL and other locations where it had a negative effect such that a unit increase in water color resulted in a 2 μg/L decrease in CHL. In addition, the spatial scales that captured variation in TP and water color effects were different for our study lakes. Variation in TP–CHL relationships was observed at intermediate distances (~20 km) compared to variation in water color–CHL relationships that was observed at regional distances (~200 km). These results demonstrate that there are lake-to-lake differences in the effects of TP and water color on lake CHL and that this variation is spatially structured. Quantifying spatial structure in these relationships furthers our understanding of the variability in these relationships at macroscales and would improve model prediction of chlorophyll a to better meet lake management goals.
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Affiliation(s)
- C. Emi Fergus
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, United States of America
- * E-mail:
| | - Andrew O. Finley
- Departments of Forestry and Geography, Michigan State University, East Lansing, Michigan, United States of America
| | - Patricia A. Soranno
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, United States of America
| | - Tyler Wagner
- U.S. Geological Survey, Pennsylvania Cooperative Fish & Wildlife Research Unit, Pennsylvania State University, University Park, Pennsylvania, United States of America
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44
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Elliott KC, Cheruvelil KS, Montgomery GM, Soranno PA. Conceptions of Good Science in Our Data-Rich World. Bioscience 2016; 66:880-889. [PMID: 29599533 PMCID: PMC5862324 DOI: 10.1093/biosci/biw115] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Scientists have been debating for centuries the nature of proper scientific methods. Currently, criticisms being thrown at data-intensive science are reinvigorating these debates. However, many of these criticisms represent long-standing conflicts over the role of hypothesis testing in science and not just a dispute about the amount of data used. Here, we show that an iterative account of scientific methods developed by historians and philosophers of science can help make sense of data-intensive scientific practices and suggest more effective ways to evaluate this research. We use case studies of Darwin's research on evolution by natural selection and modern-day research on macrosystems ecology to illustrate this account of scientific methods and the innovative approaches to scientific evaluation that it encourages. We point out recent changes in the spheres of science funding, publishing, and education that reflect this richer account of scientific practice, and we propose additional reforms.
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Affiliation(s)
- Kevin C Elliott
- Kevin C. Elliott is an associate professor in Lyman Briggs College, the Department of Fisheries and Wildlife, and the Department of Philosophy; Kendra S. Cheruvelil is an associate professor in Lyman Briggs College and the Department of Fisheries and Wildlife; Georgina M. Montgomery is an associate professor in Lyman Briggs College and the Department of History; and Patricia A. Soranno is a professor in the Department of Fisheries and Wildlife at Michigan State University, in East Lansing. All authors contributed equally to the conceptualization of the paper and the supporting research. KCE organized the collaboration and initiated the writing process. All authors contributed text, reviewed manuscript drafts, and approved the final version
| | - Kendra S Cheruvelil
- Kevin C. Elliott is an associate professor in Lyman Briggs College, the Department of Fisheries and Wildlife, and the Department of Philosophy; Kendra S. Cheruvelil is an associate professor in Lyman Briggs College and the Department of Fisheries and Wildlife; Georgina M. Montgomery is an associate professor in Lyman Briggs College and the Department of History; and Patricia A. Soranno is a professor in the Department of Fisheries and Wildlife at Michigan State University, in East Lansing. All authors contributed equally to the conceptualization of the paper and the supporting research. KCE organized the collaboration and initiated the writing process. All authors contributed text, reviewed manuscript drafts, and approved the final version
| | - Georgina M Montgomery
- Kevin C. Elliott is an associate professor in Lyman Briggs College, the Department of Fisheries and Wildlife, and the Department of Philosophy; Kendra S. Cheruvelil is an associate professor in Lyman Briggs College and the Department of Fisheries and Wildlife; Georgina M. Montgomery is an associate professor in Lyman Briggs College and the Department of History; and Patricia A. Soranno is a professor in the Department of Fisheries and Wildlife at Michigan State University, in East Lansing. All authors contributed equally to the conceptualization of the paper and the supporting research. KCE organized the collaboration and initiated the writing process. All authors contributed text, reviewed manuscript drafts, and approved the final version
| | - Patricia A Soranno
- Kevin C. Elliott is an associate professor in Lyman Briggs College, the Department of Fisheries and Wildlife, and the Department of Philosophy; Kendra S. Cheruvelil is an associate professor in Lyman Briggs College and the Department of Fisheries and Wildlife; Georgina M. Montgomery is an associate professor in Lyman Briggs College and the Department of History; and Patricia A. Soranno is a professor in the Department of Fisheries and Wildlife at Michigan State University, in East Lansing. All authors contributed equally to the conceptualization of the paper and the supporting research. KCE organized the collaboration and initiated the writing process. All authors contributed text, reviewed manuscript drafts, and approved the final version
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45
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Wagner T, Fergus CE, Stow CA, Cheruvelil KS, Soranno PA. The statistical power to detect cross‐scale interactions at macroscales. Ecosphere 2016. [DOI: 10.1002/ecs2.1417] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Affiliation(s)
- Tyler Wagner
- U.S. Geological SurveyPennsylvania Cooperative Fish and Wildlife Research UnitThe Pennsylvania State University University Park Pennsylvania 16802 USA
| | - C. Emi Fergus
- Department of Fisheries and WildlifeMichigan State University East Lansing Michigan 48824 USA
| | - Craig A. Stow
- NOAA Great Lakes Laboratory Ann Arbor Michigan 48108 USA
| | - Kendra S. Cheruvelil
- Department of Fisheries and WildlifeMichigan State University East Lansing Michigan 48824 USA
- Lyman Briggs CollegeMichigan State University East Lansing Michigan 48825 USA
| | - Patricia A. Soranno
- Department of Fisheries and WildlifeMichigan State University East Lansing Michigan 48824 USA
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46
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Davies N, Field D, Gavaghan D, Holbrook SJ, Planes S, Troyer M, Bonsall M, Claudet J, Roderick G, Schmitt RJ, Zettler LA, Berteaux V, Bossin HC, Cabasse C, Collin A, Deck J, Dell T, Dunne J, Gates R, Harfoot M, Hench JL, Hopuare M, Kirch P, Kotoulas G, Kosenkov A, Kusenko A, Leichter JJ, Lenihan H, Magoulas A, Martinez N, Meyer C, Stoll B, Swalla B, Tartakovsky DM, Murphy HT, Turyshev S, Valdvinos F, Williams R, Wood S. Simulating social-ecological systems: the Island Digital Ecosystem Avatars (IDEA) consortium. Gigascience 2016; 5:14. [PMID: 26998258 PMCID: PMC4797119 DOI: 10.1186/s13742-016-0118-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2015] [Accepted: 02/21/2016] [Indexed: 12/21/2022] Open
Abstract
Systems biology promises to revolutionize medicine, yet human wellbeing is also inherently linked to healthy societies and environments (sustainability). The IDEA Consortium is a systems ecology open science initiative to conduct the basic scientific research needed to build use-oriented simulations (avatars) of entire social-ecological systems. Islands are the most scientifically tractable places for these studies and we begin with one of the best known: Moorea, French Polynesia. The Moorea IDEA will be a sustainability simulator modeling links and feedbacks between climate, environment, biodiversity, and human activities across a coupled marine–terrestrial landscape. As a model system, the resulting knowledge and tools will improve our ability to predict human and natural change on Moorea and elsewhere at scales relevant to management/conservation actions.
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Affiliation(s)
- Neil Davies
- Gump South Pacific Research Station, University of California Berkeley, Moorea, BP 244 98728 French Polynesia ; Biodiversity Institute, Department of Zoology, University of Oxford, The Tinbergen Building, South Parks Road, Oxford, OX1 3PS UK ; Berkeley Institute for Data Science,190 Doe Library, University of California, Berkeley, CA 94720 USA
| | - Dawn Field
- Biodiversity Institute, Department of Zoology, University of Oxford, The Tinbergen Building, South Parks Road, Oxford, OX1 3PS UK
| | - David Gavaghan
- Computational Biology Group, Department of Computer Science, University of Oxford, Wolfson Building, Oxford, UK
| | - Sally J Holbrook
- Department of Ecology, Evolution and Marine Biology and the Marine Science Institute, University of California Santa Barbara, Santa Barbara, CA 93106 USA
| | - Serge Planes
- Laboratoire d'Excellence CORAIL, USR 3278 CNRS-EPHE-UPVD, Centre de Recherche Insulaire et Observatoire de l'Environnement (CRIOBE), Papetoai, Moorea BP 1013 - 98 729 French Polynesia
| | - Matthias Troyer
- Institute for Theoretical Physics and Platform for Advanced Scientific Computation, ETH Zurich, Zurich, 8093 Switzerland
| | - Michael Bonsall
- Biodiversity Institute, Department of Zoology, University of Oxford, The Tinbergen Building, South Parks Road, Oxford, OX1 3PS UK
| | - Joachim Claudet
- Laboratoire d'Excellence CORAIL, USR 3278 CNRS-EPHE-UPVD, Centre de Recherche Insulaire et Observatoire de l'Environnement (CRIOBE), Papetoai, Moorea BP 1013 - 98 729 French Polynesia
| | - George Roderick
- Department of Environmental Science, Policy, & Management, 130 Mulford Hall #3114, University of California, Berkeley, CA 94720 USA
| | - Russell J Schmitt
- Department of Ecology, Evolution and Marine Biology and the Marine Science Institute, University of California Santa Barbara, Santa Barbara, CA 93106 USA
| | - Linda Amaral Zettler
- The Josephine Bay Paul Center for Comparative Molecular Biology and Evolution, Marine Biological Laboratory, Woods Hole, MA 02543 USA
| | - Véronique Berteaux
- Laboratoire d'Excellence CORAIL, USR 3278 CNRS-EPHE-UPVD, Centre de Recherche Insulaire et Observatoire de l'Environnement (CRIOBE), Papetoai, Moorea BP 1013 - 98 729 French Polynesia
| | - Hervé C Bossin
- Unit of Medical Entomology, Institut Louis Malardé, Tahiti, BP 30, 98713 French Polynesia
| | - Charlotte Cabasse
- Berkeley Institute for Data Science,190 Doe Library, University of California, Berkeley, CA 94720 USA
| | - Antoine Collin
- Ecole Pratique des Hautes Etudes, Laboratory of Coastal Geomorphology and Environment, Dinard, France
| | - John Deck
- Berkeley Natural History Museums, 3101 Valley Life Sciences Building, Berkeley, CA 94720 USA
| | - Tony Dell
- National Great Rivers Research and Education Center (NGRREC), One Confluence Way, East Alton, IL 62024 USA
| | - Jennifer Dunne
- Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501 USA
| | - Ruth Gates
- Hawaii Institute of Marine Biology, School of Ocean & Earth Science & Technology, University of Hawaii at Manoa, PO Box 1346, Kaneohe, HI 96744 USA
| | - Mike Harfoot
- United Nations Environment Programme World Conservation Monitoring Centre, 219 Huntingdon Road, Cambridge, CB3 0DL UK
| | - James L Hench
- Marine Laboratory, Nicholas School of the Environment, Duke University, 135 Marine Lab Road, Beaufort, NC 28516 USA
| | - Marania Hopuare
- Laboratoire GePaSud, Université de la Polynésie Française, Tahiti, BP6570, 98702 Faa'a French Polynesia
| | - Patrick Kirch
- Department of Anthropology, University of California, 232 Kroeber Hall, Berkeley, CA 94720 USA
| | - Georgios Kotoulas
- Institute of Marine Biology, Biotechnology and Aquaculture Hellenic Centre for Marine Research Gournes Pediados, PO Box 2214, Heraklion, Crete GR 710 03 Greece
| | - Alex Kosenkov
- Institute for Theoretical Physics and Platform for Advanced Scientific Computation, ETH Zurich, Zurich, 8093 Switzerland
| | - Alex Kusenko
- Department of Physics and Astronomy, University of California, 475 Portola Plaza, Los Angeles, CA 90095 USA
| | - James J Leichter
- Scripps Institution of Oceanography, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA
| | - Hunter Lenihan
- Bren School of Environmental Science and Management, 3428 Bren Hall, University of California, Santa Barbara, CA 93106 USA
| | - Antonios Magoulas
- Institute of Marine Biology, Biotechnology and Aquaculture Hellenic Centre for Marine Research Gournes Pediados, PO Box 2214, Heraklion, Crete GR 710 03 Greece
| | - Neo Martinez
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85721 USA ; Pacific Ecoinformatics and Computational Ecology Lab, Berkeley, CA 94703 USA
| | - Chris Meyer
- Department of Invertebrate Zoology, National Museum of Natural History, Smithsonian Institution, PO Box 37012, MRC-163, Washington, DC 20013 USA
| | - Benoit Stoll
- Laboratoire GePaSud, Université de la Polynésie Française, Tahiti, BP6570, 98702 Faa'a French Polynesia
| | - Billie Swalla
- Friday Harbor Laboratories, University of Washington, 620 University Road, Friday Harbor, WA 98250 USA
| | - Daniel M Tartakovsky
- Department of Mechanical and Aerospace Engineering, University of California San Diego, 9500 Gilman Drive, Mail Code 0411, La Jolla, CA 92093 USA
| | - Hinano Teavai Murphy
- Atitia Center, Gump Station, University of California Berkeley, Moorea, BP 244 98728 French Polynesia
| | - Slava Turyshev
- NASA Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109 USA ; Department of Physics and Astronomy and Department of Earth and Planetary Sciences University of California, Los Angeles, CA 90095 USA
| | - Fernanda Valdvinos
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85721 USA
| | - Rich Williams
- Vibrant Data Inc., 943 Clay Street, San Francisco, Calfornia 94108 USA
| | - Spencer Wood
- School for Environmental and Forest Sciences, University of Washington, Box 352100, Seattle, Washington 98195 USA
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