HOW DO SCIENTISTS IN THE REAL WORLD USE TIME-SERIES DATA?
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HOW DO SCIENTISTS IN THE REAL WORLD USE TIME-SERIES DATA?
• Who collects data?
• What are some stories behind data?
• How much data is enough?
• How is the data being used?
• What is different to what we teach?
WHO COLLECTS DATA?
Many different organisations…
• Regional and local councils.
• Transit NZ.
• Research institutes e.g. NIWA
• Consulting firms e.g. BECA
• Schools.
OVERVIEW
• Importance of long term trend.
• Contexts for correlation and interpolation.
• Using one set of data to create another.
• Importance of data over long time periods.
• Different analysis techniques.
• Think about and question what we teach.
MAHURANGI HARBOUR
LONG TERM TREND
Horse mussel numbers
Wedge shell numbers
Cockle numbers
Population decline – examples1994 - 2003
Monitoring
DATA TOLD SCIENTISTS…
• Health of Mahurangi Harbour in decline.
• Increased sedimentation was smothering marine life and causing a decline in diversity.
• Common shellfish no longer found in some areas.
• Boating had become more difficult because of reduced water depths.
MAHURANGI ACTION PLAN
Goal: Halt, slow or reverse the adverse effects of sedimentation.
• Fence-off streams, waterways and wetlands.
• Undertake riparian planting.
• Conduct a sediment source assessment.
• Change land management practices.
• Extensive environmental education.
TRENDS IN LAKE TAUPO
0
100
200
300
400
500
600
700
1970 1975 1980 1985 1990 1995 2000 2005 2010
NO
3-N
(to
nn
es
)
r2 = 0.58
Trend = 11.15 t y-1
NO3-N increasing trend
ANNUAL NITRATE ACCUMULATIONTREND OR CYCLE?
A polynomial model with a 9-year cycle gives a good fit .. r2 = 0.9
0
100
200
300
400
500
600
700
800
1970 1975 1980 1985 1990 1995 2000 2005 2010
NO
3-N
(to
nn
es
)
Mo
del
pre
dic
tio
n
?
WHAT MODEL IS THE BEST FIT?
0.0
0.5
1.0
1.5
2.0
2.5
3.0
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Ch
loro
ph
yll a
(m
g m
-3)
In the last 10 years, mean chlorophyll a concentrations have more than doubled
OTHER EVIDENCE
0.0
0.5
1.0
1.5
2.0
2.5
3.0
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Ch
loro
ph
yll a
(m
g m
-3)
Maximum
Average
Minimum0.18 ± 0.07 mg m-3 y-1
0.072 ± 0.027 mg m-3 y-1
Summer(r2 = 0.57)
Winter(r2 = 0.78)
Annual Average(r2 = 0.77)
FURTHER ANALYSIS
Goal: Reduce nitrogen run off by 20%.
• Regional plan change.
• Launch an $81.5 million fund.
• Encourage and assist land use change.
• More restrictive wastewater practices.
PROTECTING LAKE TAUPO STRATEGY
SH20 WATERVIEW CONNECTION
A 3.2 km tunnel to connect SH20 at Maioro St in Mt Roskill to the northwestern motorway SH16 at Waterview by Great South Rd
PRIOR KNOWLEDGE TO INFORM PLANNING
• In drilling this tunnel, how much ground water will be removed?
• What effects will this have on the flow and ecosystem of Oakley Creek?
• What are the usual flow levels in Oakley Creek?
• What monitoring information is available on flow rates of Oakley Creek?
USING ONE SET OF TIME-SERIES DATA TO CREATE ANOTHER
• Use flow rates from a monitored creek in a nearby catchment.
• Check relationship with the small amount of flow data from Oakley Creek.
• Generate Oakley Creek flow data set.
• Use this as input for groundwater models.
• Establish impact on ecosystem.
CORRELATING DATA
WHAT IS THE NORMAL ANNUAL CYCLE?
ANOMALIES
HOW MUCH DATA IS ENOUGH?
JUST USE THE MOST RECENT DATA?
SEA LEVEL RISE - PROJECTIONS
SEA LEVEL ANOMALIES 1974 - 2006
SEA LEVEL ANOMALIES 2001 -2007
SEA LEVEL ANOMALIES 1973 - 1994
WITHIN OUR CURRICULUM - DO WE TEACH THIS?
• Establish a relationship between two data sets and then use one set to complete another.
• Graphs or diagrams based on anomalies.
• Different time – series analysis.
ANOMALIES
WAS MAY HOTTER THAN USUAL?
• http://www.niwa.co.nz/edu/resources/climate
• http://cliflo-niwa.niwa.co.nz/
DateTemp
Ma x (C)Anomalyfor May
1 21.7 4.3
2 19.3 1.9
3 18.9 1.5
4 17.7 0.3
5 16.9 -0.5
6 20.2 2.8
7 17.3 -0.1
8 17.9 0.5
9 19.2 1.8
10 17.6 0.2
YES!
26 days were warmer than average for May and only 5 days were colder than average.
DENDROCHRONOLOGY TREE + TIME-STUDY
• Oxygen isotope signal correlates to temperature.
• Ring-width correlates to periods of low river flow.
• Useful for improving climate model results.