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Valuation of Ecosystem services for EBM - Update by Susanne Menzel
Economic valuation and EBM
-update-
Manuscript
Version 20.x
Missing: application/study case
Content
Reminder of activity based valuation for EBM
Study case: what we have and what is missing
‘Needs’
Reminder
Economic valuation studies so far not very useful for EBM
Ecosystem services based approaches so far assume system knowledge that is unavailable/not analysed
We think we can provide a useful –new- approach
Comments/contributions
Very welcome!
Study case Kelp forest CA
‘Hypothesis’ about ecosystem services based on available knowledge
Aim of study case
Illustration usefulness and practicability of approach
Quantification of contribution of ecological elements to benefit of activities
For all activities we want to get at
‘total commercial value’ at different places
drivers of benefit (man-made, ecological)
expected change of commercial value when ecological quality changes
Many challenges
Data for different activities seems only available on different scales
Character of activities are very different
Non-consumptive recreational (diving)
‘productive’ (commercial fishing)
Consumptive recreational (recreational fishing)
 Risk of comparing ‘apples and oranges’
Diving
‘experience based’, non-consumptive activity
time based ‘benefit’ approach (fixed financial costs per trip)
‘benefits of spot’ = # dives x costs per dive
different dive spots ‘compete’ (travel distance and ‘eco-quality’)
# dives = f (ecological quality, man made features, [available human population])
Data and analysis - Diving
We have (Monterey) :
# of dives per spot
ecological data for PISCO sites
Kelp cover
Price per dive from dive survey (~ $-US 25)
Distance from harbor (?)
Challenge I - linking PISCO sites to dive sites
8 PISCO sites
14 diving spots
Only 6 ‘common/shared’ places (# of cases for analysis)
Challenge II - shore dives vs. boat dives
Nested decision (1st: decision boat or shore, 2nd: where)… Two models?
If two models: further reduction of # of cases: boat ( 4), shore (2)
 analysis? …. df �; alternative: use only kelp cover as indicator for ecological quality? Or comparison of models with different ecological parameter
Commercial fishing
Consumptive activity
Catch and effort based approach
(species specific) landings x (species specific) value – costs of fishing = net commercial value
Data and analysis - commercial fishing
We have:
Monterey commercial landings 1999-2005 (Irit!)
Requested data
Near shore finfish reports of catch by port and block (CA DFG) (Carrie?)
Missing!
Effort
Higher resolution data for Monterey
Indicator for ‘eco-quality: kelp cover, what other ecological data is available on same scale?
Analysis:
simple: net commercial values for different regions linked to sub-ports/ports
Regression: drivers for net commercial value (kelp cover, …)
Recreational fishing
“Experience based and consumptive� activity
 need time and output based approach
“Benefits of spot� time or catch based?
Challenge: searching time vs. fishing time
‘benefits of spot’ = # hrs/catch x costs per trip
Catch & hrs fished = f (ecological quality, man made features, available human population)
Recreational fishing (cont.)
LA vs. Humboldt-area: at ‘lower’-quality spot (catch) in LA many more hours were spent than at ‘higher’ quality area in Humboldt-area.
What defines benefit of spot hrs fished or catch?
In cross-county comparison: average catch doesn’t seem to drive recreational fishing activity (possibly space issue: places do not really compete!)
Can we merge the dimensions time and catch? How? If we can’t merge, what do we use?
Data - recreational fishing
We have
Total expenditure of marine recreational fishing for Southers CA and for Nothern CA in 2000 (Steinback et al. 2004)
E.g. boat fuel SCA $-US 23,220,000
Hours spend fishing (county level) (RecFin)
Mean catch per hour (county level) (RecFin)
Ecological data?: kelp cover
We need:
Better spatial resolution for recreational fishing data (Monterey data)
‘Eco-quality’ data
Additional challenge for ‘3-activities’ analysis
Scale and spatial distribution of activity!
Diving: point activity & point data
Commercial and recreational/sport fishing: point or spatially “spread� activity (depends on gear, species)
Boundaries: additional to ecological dimensions it could be helpful to use clusters of human populations to define boundaries. This way ‘competing places’ can be identified and subsequently drivers of activities. (‘spatially shifting baseline’)
Needs
Help.
In further data gathering/ecological data sharing
Finding solution to dealing with spatial dimension of activities
Analysis
Comments from economists
Species II
Species I
Activity III
Human need I
+
+
Human need II
Human need III
Activity II
Activity I
-
Species III
-
-
-
+
0
0/-
+
-
+
-
Activity IV
+
+
+
+
+
+
+
Blue: type A ecosystem services, green type B ecosystem services, red: threat
Source: RecFin
Created with pptHtml
-update-
Manuscript
Version 20.x
Missing: application/study case
Content
Reminder of activity based valuation for EBM
Study case: what we have and what is missing
‘Needs’
Reminder
Economic valuation studies so far not very useful for EBM
Ecosystem services based approaches so far assume system knowledge that is unavailable/not analysed
We think we can provide a useful –new- approach
Comments/contributions
Very welcome!
Study case Kelp forest CA
‘Hypothesis’ about ecosystem services based on available knowledge
Aim of study case
Illustration usefulness and practicability of approach
Quantification of contribution of ecological elements to benefit of activities
For all activities we want to get at
‘total commercial value’ at different places
drivers of benefit (man-made, ecological)
expected change of commercial value when ecological quality changes
Many challenges
Data for different activities seems only available on different scales
Character of activities are very different
Non-consumptive recreational (diving)
‘productive’ (commercial fishing)
Consumptive recreational (recreational fishing)
 Risk of comparing ‘apples and oranges’
Diving
‘experience based’, non-consumptive activity
time based ‘benefit’ approach (fixed financial costs per trip)
‘benefits of spot’ = # dives x costs per dive
different dive spots ‘compete’ (travel distance and ‘eco-quality’)
# dives = f (ecological quality, man made features, [available human population])
Data and analysis - Diving
We have (Monterey) :
# of dives per spot
ecological data for PISCO sites
Kelp cover
Price per dive from dive survey (~ $-US 25)
Distance from harbor (?)
Challenge I - linking PISCO sites to dive sites
8 PISCO sites
14 diving spots
Only 6 ‘common/shared’ places (# of cases for analysis)
Challenge II - shore dives vs. boat dives
Nested decision (1st: decision boat or shore, 2nd: where)… Two models?
If two models: further reduction of # of cases: boat ( 4), shore (2)
 analysis? …. df �; alternative: use only kelp cover as indicator for ecological quality? Or comparison of models with different ecological parameter
Commercial fishing
Consumptive activity
Catch and effort based approach
(species specific) landings x (species specific) value – costs of fishing = net commercial value
Data and analysis - commercial fishing
We have:
Monterey commercial landings 1999-2005 (Irit!)
Requested data
Near shore finfish reports of catch by port and block (CA DFG) (Carrie?)
Missing!
Effort
Higher resolution data for Monterey
Indicator for ‘eco-quality: kelp cover, what other ecological data is available on same scale?
Analysis:
simple: net commercial values for different regions linked to sub-ports/ports
Regression: drivers for net commercial value (kelp cover, …)
Recreational fishing
“Experience based and consumptive� activity
 need time and output based approach
“Benefits of spot� time or catch based?
Challenge: searching time vs. fishing time
‘benefits of spot’ = # hrs/catch x costs per trip
Catch & hrs fished = f (ecological quality, man made features, available human population)
Recreational fishing (cont.)
LA vs. Humboldt-area: at ‘lower’-quality spot (catch) in LA many more hours were spent than at ‘higher’ quality area in Humboldt-area.
What defines benefit of spot hrs fished or catch?
In cross-county comparison: average catch doesn’t seem to drive recreational fishing activity (possibly space issue: places do not really compete!)
Can we merge the dimensions time and catch? How? If we can’t merge, what do we use?
Data - recreational fishing
We have
Total expenditure of marine recreational fishing for Southers CA and for Nothern CA in 2000 (Steinback et al. 2004)
E.g. boat fuel SCA $-US 23,220,000
Hours spend fishing (county level) (RecFin)
Mean catch per hour (county level) (RecFin)
Ecological data?: kelp cover
We need:
Better spatial resolution for recreational fishing data (Monterey data)
‘Eco-quality’ data
Additional challenge for ‘3-activities’ analysis
Scale and spatial distribution of activity!
Diving: point activity & point data
Commercial and recreational/sport fishing: point or spatially “spread� activity (depends on gear, species)
Boundaries: additional to ecological dimensions it could be helpful to use clusters of human populations to define boundaries. This way ‘competing places’ can be identified and subsequently drivers of activities. (‘spatially shifting baseline’)
Needs
Help.
In further data gathering/ecological data sharing
Finding solution to dealing with spatial dimension of activities
Analysis
Comments from economists
Species II
Species I
Activity III
Human need I
+
+
Human need II
Human need III
Activity II
Activity I
-
Species III
-
-
-
+
0
0/-
+
-
+
-
Activity IV
+
+
+
+
+
+
+
Blue: type A ecosystem services, green type B ecosystem services, red: threat
Source: RecFin
Created with pptHtml