| 1. |
- Soranno, Patricia A., et al.
(författare)
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LAGOS-NE : A multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of U.S. lakes
- 2017
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Ingår i: GigaScience. - : Oxford University Press (OUP). - 2047-217X. ; 6:12, s. 1-22
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Tidskriftsartikel (refereegranskat)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 51101 lakes and reservoirs larger than 4 ha in 17 lake-rich US states. The database includes 3 datamodules 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 situmeasurements of lake water quality for a subset of the lakes fromthe past 3 decades for approximately 2600–12 000 lakes depending on the variable. The database contains approximately 150000 measures of total phosphorus, 200 000 measures of chlorophyll, and 900 000 measures of Secchi depth. The water quality data were compiled from87 lake water quality data sets fromfederal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. This database is one of the largest andmost comprehensive databases of its type because it includes both in situmeasurements 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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| 2. |
- Lapierre, Jean-Francois, et al.
(författare)
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Similarity in spatial structure constrains ecosystem relationships : Building a macroscale understanding of lakes
- 2018
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Ingår i: Global Ecology and Biogeography. - : John Wiley & Sons. - 1466-822X .- 1466-8238. ; 27:10, s. 1251-1263
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Tidskriftsartikel (refereegranskat)abstract
- Aim: We aimed to measure the dominant spatial patterns in ecosystem properties (such as nutrients and measures of primary production) and the multi‐scaled geographical driver variables of these properties and to quantify how the spatial structure of pattern in all of these variables influences the strength of relationships among them.Location and time period: We studied > 8,500 lakes in a 1.8 million km2 area of Northeast U.S.A. Data comprised 10‐year medians (2002–2011) for measured ecosystem properties, long‐term climate averages and recent land use/land cover variables.Major taxa studied: We focused on ecosystem properties at the base of aquatic food webs, including concentrations of nutrients and algal pigments that are proxies of pri -mary productivity.Methods: We quantified spatial structure in ecosystem properties and their geograph-ical driver variables using distance‐based Moran eigenvector maps (dbMEMs). We then compared the similarity in spatial structure for all pairs of variables with the cor -relation between variables to illustrate how spatial structure constrains relationships among ecosystem properties.Results: The strength of spatial structure decreased in order for climate, land cover/use, lake ecosystem properties and lake and landscape morphometry. Having a compa -rable spatial structure is a necessary condition to observe a strong relationship be -tween a pair of variables, but not a sufficient one; variables with very different spatial structure are never strongly correlated. Lake ecosystem properties tended to have an intermediary spatial structure compared with that of their main drivers, probably be -cause climate and landscape variables with known ecological links induce spatial patterns.Main conclusions: Our empirical results describe inherent spatial constraints that dic -tate the expected relationships between ecosystem properties and their geographical drivers at macroscales. Our results also suggest that understanding the spatial scales at which ecological processes operate is necessary to predict the effects of multi‐scaled environmental changes on ecosystem properties.
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