Building Capacity and Linking Infrastructure in the Lake and Coral Reef Scientific Communities    

 7-9 March 2005     Scripps Institution of Oceanography - San Diego, California USA

 

Day one Notes

 

 

 

Building capacity and linking infrastructure in the lake and scientific community

 

Monday 7 March

 

Afternoon session: Breakout group: Lake Observatory Community

 

Tasks:

 

 

 

 

 

 

 

Issues arising:

Computer science, IT, cyberinfrastructure:

-         One aspect is what is the reliability issue that is preventing the science from being best addressed properly.

-         Engineering aspects (rather than IT) should be an integral part of the discussion.

Outcome is what are the barriers that are preventing the science from being addressed.

 

(What is not being addressed through the science technology)

 

 

 

Questions:

 

1)      What role do physical factors play in structuring biological (e.g. algal) communities and how this vary across broad temporal and spatial scales

2)      What role do episodic climatic events play in structuring biological communities

Barriers:

Logistics/technology

Data management (how to manage, store and access a lot of data)?

 

 

1)      I have a very good answer.  Do you have a good question for me?

 

 

1)      How does physical limnology control biology

2)      How do we gain a greater confidence in biological parameters used in modeling?

Barriers:

Lack of spatial/temporal resolution of biological compared with scales of processes.

Different process descriptions and model set-ups lead to different calibration of parameters.

 

1)      How can we easily accommodate change in sensor configuration/buoy deployment in an automated manner?

2)      How can we accomplish QA/QC on large amounts of real time data?

Barriers:

Data structure for sensors and tools to generate all subsequent schema changes, QA/QC etc.

Lack of tools, algorithms that no not require manual inspection.

 

1)      Coherence on regional/national/global scales of physical/chemical/biological variables.  Can we use selected sites to inform us of wider selection of lakes.

2)      Spatial variability.  How many locations withn a lake system do we need to monitor?

Barriers:

Methods for sensing biological communities

Reliability - sensor fouling/fault tolerance etc.

 

1)      The most concerning question is how we can set up automated data collection system for the specific question to be addressed?  Different questions need different sensors for addressing different lakes.

Barriers:

Networking is necessary but is not the urgent issue so far.

 

1)      Does it mean anything to transfer data before the issue of multiple vs one station in a lake is addressed.

2)      How do you define lake metabolism in an alkaline lake where HCO3 predominates C uptake?

 

1)      Can we determine which lakes are acting coherently globally, e.g. stratification patterns

2)      Phytoplankton dynamics: are there common factors which drive the vertical distributions of phytoplankton on a global scale.

Barriers:

Standard spacing of temperature loggers and standard timing of sensors

Fluorescence probes are not in common usage. Would like to distinguish different phytoplankton groups and vertical spacing of probes.

 

1)      Across scales ranging from second to weeks, what controls dissolved oxygen?

2)      How do different habitats contribute to whole lake metabolism?

 

1)      Can we predict the succession of phytoplankton (species/taxa/biomass) in a lake in response to changes in environment variables?

2)      Can we decipher physical/chemical//biological signals in an observed biological response.

Barriers:

Personnel with truly inter-disciplinary skills (modelers, IT/ecologists)

Funding

 

1)      When and where do episodic events occurs that lend to enhanced metabolism (baterial, phytoplankton, zooplankton) activity?  How do these events compare relative to many scale ones to overall ecosystem function?  How do we design sampling strategies to capture episodic events?

2)      Are episodic events an important component of climate change?  How do their impacts compare to human influences on the landscape?  Can human activities lead to intensified effects of events?

Barriers: What are the aspects of modeling that need improvement in order to accurately describe system response?

Good underwater communication merge of data streams, QA/QC of logged data.

Linkages among landscape elements - inexpensive units that capture essential data and which can relay data to convenien notes (e.g. sampling rivers during ice break-up).

 

1)      Adaptive sampling: what are the needs for adaptive sampling?  How "real time" does sampling need to be?

Barrier: Human control versus computer control

2)      Underwater wireless: What are the uses for this?

Barrier: This is hard (but exciting) multidisciplinary engineering problem.  Is it worth the effort?

 

1)      What is the role of non-hydrostatic pressure on lake

2)      What is the role of circulation of biological productivity?

Non-hydrostatic model may require parallelization?

Once we have a model how can we automate the process of calibration?

 

1)      Stability of data communication under the influence of weather systems?

2)      Adjustable data scheme to automatically accommodate measured changes?

 

1)      To collect data of temporal and spatial variability of limnological factors

2)      Can short-term variation of temperature, DO be t

 

1)      What is the variability of observed data in the lakes compared to that in terrestrial systems and that amongst continents?

Do you have the time scales and adequate data that can deal with the questions of concern?

 

1)      How do episodic events occurring over relatively short time scales (e.g. internal waves) affect the biological components of lake ecosystems (both short- and long-term)

2)      What characteristics of lakes constrain the responses to these episodic events?

3)      What ways of characterizing events provide insight into biological responses across event types?

Barriers

Need for sensors that detect short-term biological responses

Need for algorithms to analyse data streams to detect episodic events?

 

1)      How does the variation in DOC load  (under changing climate) affect lake productivity (P:R ratio)

2)      The reposnse of lake productivity and C fluxes to extreme weather evcents (including short-term)

Barriers

Representative sest of sites with different land use and climate

Synchronized intensive monitoring of key variables (with comparable, "identical"h sensors/devices)

 

 

1)      Meta-definitions

2)      Policies for pesquire spaing (data services)

3)      Core set of scenarios to derive requirements (e.g. cross-site query)

4)      Development plans - resources and priorities

5)      Core technology (e.g. RDMS, web )

Barriers

Community agreement

IT Resources (physical software, people)

1)What role do physical factors play in structuring biological (e.g. algal) communities and how this vary across broad temporal and spatial scales

2) What role do episodic climatic events play in structuring biological communities

Barriers:

Logistics/technology

Data management (how to manage, store and access a lot of data)?

 

 

2)      I have a very good answer.  Do you have a good question for me?

 

 

3)      How does physical limnology control biology

4)      How do we gain a greater confidence in biological parameters used in modeling?

Barriers:

Lack of spatial/temporal resolution of biological compared with scales of processes.

Different process descriptions and model set-ups lead to different calibration of parameters.

 

3)      How can we easily accommodate change in sensor configuration/buoy deployment in an automated manner?

4)      How can we accomplish QA/QC on large amounts of real time data?

Barriers:

Data structure for sensors and tools to generate all subsequent schema changes, QA/QC etc.

Lack of tools, algorithms that no not require manual inspection.

 

3)      Coherence on regional/national/global scales of physical/chemical/biological variables.  Can we use selected sites to inform us of wider selection of lakes.

4)      Spatial variability.  How many locations withn a lake system do we need to monitor?

Barriers:

Methods for sensing biological communities

Reliability - sensor fouling/fault tolerance etc.

 

2)      The most concerning question is how we can set up automated data collection system for the specific question to be addressed?  Different questions need different sensors for addressing different lakes.

Barriers:

Networking is necessary but is not the urgent issue do far.

 

3)      Does it mean anything to transfer data before the issue of multiple vs one station in a lake is addressed.

4)      How do you define lake metabolism in an alkaline lake where HCO3 predominates C uptake?

 

3)      Can we determine which lakes are acting coherently globally, e.g. stratification patterns

4)      Phytoplankton dynamics: are there common factors which drive the vertical distributions of phytoplankton on a global scale.

Barriers:

Standard spacing of temperature loggers and standard timing of sensors

Fluorescence probes are not in common usage. Would like to distinguish different phytoplankton groups and vertical spacing of probes.

 

3)      Across scales ranging from second to weeks, what controls dissolved oxygen?

4)      How do different habitats contribute to whole lake metabolism?

 

3)      Can we predict the succession of phytoplankton (species/taxa/biomass) in a lake in response to changes in environment variables?

4)      Can we decipher physical/chemical//biological signals in an observed biological response.

Barriers:

Personnel with truly inter-disciplinary skills (modelers, IT/ecologists)

Funding

 

3)      When and where do episodic events occurs that lend to enhanced metabolism (baterial, phytoplankton, zooplankton) activity?  How do these events compare relative to many scale ones to overall ecosystem function?  How do we design sampling strategies to capture episodic events?

4)      Are episodic events an important component of climate change?  How do their impacts compare to human influences on the landscape?  Can human activities lead to intensified effects of events?

Barriers: What are the aspects of modeling that need improvement in order to accurately describe system response?

Good underwater communication merge of data streams, QA/QC of logged data.

Linkages among landscape elements - inexpensive units that capture essential data and which can relay data to convenien notes (e.g. sampling rivers during ice break-up).

 

3)      Adaptive sampling: what are the needs for adaptive sampling?  How "real time" does sampling need to be?

Barrier: Human control versus computer control

4)      Underwater wireless: What are the uses for this?

Barrier: This is hard (but exciting) multidisciplinary engineering problem.  Is it worth the effort?

 

3)      What is the role of non-hydrostatic pressure on lake

4)      What is the role of circulation of biological productivity?

Non-hydrostatic model may require parallelization?

Once we have a model how can we automate the process of calibration?

 

3)      Stability of data communication under the influence of weather systems?

4)      Adjustable data scheme to automatically accommodate measured changes?

 

3)      To collect data of temporal and spatial variability of limnological factors

4)      Can short-term variation of temperature, DO be t

 

2)      What is the variability of observed data in the lakes compared to that in terrestrial systems and that amongst continents?

Do you have the time scales and adequate data that can deal with the questions of concern?

 

4)      How do episodic events occurring over relatively short time scales (e.g. internal waves) affect the biological components of lake ecosystems (both short- and long-term)

5)      What characteristics of lakes constrain the responses to these episodic events?

6)      What ways of characterizing events provide insight into biological responses across event types?

Barriers

Need for sensors that detect short-term biological responses

Need for algorithms to analyse data streams to detect episodic events?

 

3)      How does the variation in DOC load  (under changing climate) affect lake productivity (P:R ratio)

4)      The reposnse of lake productivity and C fluxes to extreme weather evcents (including short-term)

Barriers

Representative sest of sites with different land use and climate

Synchronized intensive monitoring of key variables (with comparable, "identical"h sensors/devices)

 

 

6)      Meta-definitions

7)      Policies for pesquire spaing (data services)

8)      Core set of scenarios to derive requirements (e.g. cross-site query)

9)      Development plans - resources and priorities

10)  Core technology (e.g. RDMS, web )

Barriers

Community agreement

IT Resources (physical software, people)

Coherent themes arising

1)    Interactions of physical and biogeochemical processes across time and space scales.  How to overlay temporal variability and achieve interpolation to spatial variability?... Are we using the right metric for metabolism and what controls dissolved oxygen across spatial and temporal scales?

2)    The role of episodic events in structuring ecological processes;

3)    Complexity of interdisciplinary models (non-hydrostatic) and the difficulties of calibrating these models, particularly with respect to ecological parameters in physical-biological models.

4)    (no takers: Relative importance of global/regional/local drivers of coherence of physical and biogeochemical processes;)