[Esip-envirosensing] Fwd: [ECOLOG-L] ASLO-SFS Session SS52

[Renee F. Brown]

An upcoming abstract deadline for a session of interest to those working in aquatic systems.

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From: "Jonathan Stetler" <privateemail319917 at community.esa.org<mailto:privateemail319917 at community.esa.org>>
Subject: [ECOLOG-L] ASLO-SFS Session SS52
Date: March 3, 2020 at 1:42:45 PM MST
To: ECOLOG-L at community.esa.org<mailto:ECOLOG-L at community.esa.org>
Reply-To: ECOLOG-L-moderator at community.esa.org<mailto:ECOLOG-L-moderator at community.esa.org>

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We are emailing to let you know about an exciting special session
we have planned at ASLO-SFS 2020 In Madison, WI, USA. Abstracts are due 9 March.

SS52 Synthesizing across time: Bridging the gap between long-term and high-frequency data

The collection of long-term ecological data is irreplaceable and has enabled the discovery of long-standing and often unexpected patterns in all types of aquatic ecosystems. Long-term data is often collected at the monthly time scale (or even less frequently), which often enables sustained monitoring over years to decades. However, ecosystems often exhibit changes at much shorter time scales. Essential changes in key ecological processes can occur within minutes to hours. These changes have the potential to play a large role in driving long-term changes and can often be difficult to detect with low-frequency long-term data. With the technological advances over the past decade, high-frequency data collection is now not only possible, but also affordable for many aquatic researchers. Coupling traditional long-term data collection with high-frequency sensor data, surveys, models, and experiments offers a path forward for researchers to synthesize drivers of environmental
change across time scales from seconds to hours to decades. Here, we strive to bring together a community of researchers whose research crosses time scales to offer new insight into the drivers and patterns of environmental change in aquatic systems. We invite researchers from both lentic and lotic systems across physical, chemical, and biological domains to share projects derived from the use of both long-term and high frequency data, surveys, experiments, and/or modeling efforts.

Jonathan Stetler, Rensselaer Polytechnic Institute, stetlj at rpi.edu<mailto:stetlj at rpi.edu>
Emily Stanley, University of Wisconsin, ehstanley at wisc.edu<mailto:ehstanley at wisc.edu>
Kevin Rose, Rensselaer Polytechnic Institute, rosek4 at rpi.edu<mailto:rosek4 at rpi.edu>
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