Daniela Miteva Brian Murray Subhrendu Pattanayak Duke University.
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Transcript of Daniela Miteva Brian Murray Subhrendu Pattanayak Duke University.
Evaluating the impacts of protected areas on ecosystem services in Indonesia: In Search of Spatial Complementarities
Daniela MitevaBrian MurraySubhrendu Pattanayak
Duke University
Should protected areas work?
Non-random location of protected areas Tend to be established on “rock and ice”
Spillover effects Extraction activities may be displaced to
the buffer zones or other unprotected nearby areas
Different levels of protection IUCN categories I-VI Enforcement
How to evaluate the effectiveness of protected areas?
Methodology Need to compare protected units with
observationally similar unprotected units▪ This yields only an average estimate of the
impact Test for heterogeneity of the impact
Outcomes Ecosystem structure vs. function
Previous studies (1)
*Indigenous reserves and wetlands excluded
Previous studies (2)
**The study selected 5 % of each country’s PA (treatment) and an area 4 times as large to serve as control
To recap: main research questions
Do the protected areas in Indonesia protect habitats and ecosystem services?
Does the impact of protected areas vary with the characteristics of the area?
Where do the tradeoffs and complementarities occur in space?
This is still very much work in progress…
Data
Biophysical characteristics Location (distance to ports by type; proximity
to district capitals, mills and markets; slope, elevation, river length, urban vs. rural)
Climate (average temperature & precipitation, aridity index, organic content and pH levels of the soils)
Socio-economic (road length, number, area and type of timber concessions, population density, village accessibility)
Protected Areas (IUCN categories I-IV)
Why do we care about mangroves?
Provision of multiple ecosystem services Blue carbon sequestration Habitat for species Storm protection
Very rapid loss of mangroves in Indonesia
Cut for timber Cleared for aquaculture & agriculture Image source: http://aquaviews.net/scuba-guides/mangrove-diving/
Methodology
Propensity score matching (PSM) to identify observationally similar protected and unprotected villages Does not rely on a specific functional
form Reduces the dimensionality of the
matching Partial Linear Models (PLM) Sensitivity analysis & robustness
checks
Methodology (cont’d): PLM Semi-parametric regression of the form
Estimated in 2 stages Least squares on m-th order difference to estimate Non-parametric (loess) estimation for
Properties Allows some variables to enter non-parametrically Reduces the dimensionality of the problem Consistent estimation for , but the efficiency depends on the order of differencing (m)
iiii xzfy )(
)( izf
Results: Deforestation 2000-2005
Protected areas do not seem to protect forests: ATT=20.91, t=0.47 Hard to match the very high propensity
scores The impact varies Covariate
Coefficient
Organic content in the topsoil
-31.628***(5.811)
Forest area at baseline0.076***
(0.007)
Distance to the nearest mill (m)
-0.003**(0.001)
Length of the river network (m)
0.015***(0.004)*** 1%, ** 5%, *10%
R2=0.19, n=2214
The impact seems to vary non-linearly with the slope
-200
00
-100
00
01
00
00
200
00
0 10 20 30Average slope (degrees)
Deforestation 95% CI
Defo
rest
ati
on
P<0.01
Results: Mangrove loss 2000-2005
Protected areas do not seem to protect mangrove patches, either (ATT=-0.14 , t=-0.17) Hard to match the very high propensity
scores The impact varies
Covariate Coefficient
Aridity index0.0005**(0.0002)
Mangrove area @ baseline
0.0613***(0.0137)
Average slope (degrees)
-0.5618**(0.2705)
Distance to market w/ permanent structures
-0.0406*
(0.0236)*** 1%, ** 5%, *10%
R2=0.4, n=139
Impact seems to vary nonlinearly the length of the river network
-20
24
68
0 20000 40000 60000 80000 100000
Length of the river network
ATT (mangrove loss)95% CI
Mangro
ve loss
P=0.001
Lots of caveats at present… Very preliminary results
Have not looked at the year the PA was established Have not considered spatial spillovers Numerous ecosystem services still to be analyzed
Dealing with decentralization in Indonesia Constant changes of the administrative units at all
levels Institutional drivers of change
Using geospatial data Raster resolution introduces errors in the
dependent & independent variables
Bibliography
Andam, K. S., P. J. Ferraro, et al. (2008). "Measuring the Effectiveness of Protected Area Networks in Reducing Deforestation." Proceedings of the National Academy of Sciences 105(42): 16089‐16094. Andam, K. S., P. J. Ferraro, et al. (2010). "Protected Areas Reduced Poverty in Costa Rica and Thailand." Proceedings of the National Academy of Sciences 107(22): 9996‐10001. Chape, S., J. Harrison, et al. (2005). "Measuring the Extent and Effectiveness of Protected Areas as an Indicator for Meeting Global Biodiversity Targets." Philosophical Transactions of the Royal Society B: Biological Sciences 360(1454): 443‐455. Das, S. and J. R. Vincent (2009). "Mangroves protected villages and reduced death toll during Indian super
cyclone." Proceedings of the National Academy of Sciences 106(18): 7357-7360. Ferraro, P. and M. Hanauer (2011). "Protecting Ecosystems and Alleviating Poverty with Parks and Reserves: ‘Win‐Win’ or Tradeoffs?" Environmental and Resource Economics 48(2): 269‐286. Ferarro, P., M. Hanauer and K. Sims (Forthcoming). “Conditions associated with protected area success in conservation and poverty alleviation”, Proceedings of the National Academy of Sciences Ferraro, P. J. and S. K. Pattanayak (2006). "Money for Nothing? A Call for Empirical Evaluation of Biodiversity Conservation Investments." PLoS Biol 4(4): e105. Joppa, L. and A. Pfaff (2010). "Reassessing the Forest Impacts of Protection." Annals of the New York Academy of Sciences 1185(1): 135‐149. Nagendra, H. (2008). "Do Parks Work? Impact of Protected Areas on Land Cover Clearing." AMBIO: A Journal of the Human Environment 37(5): 330‐337. Naughton‐Treves, L., M. B. Holland, et al. (2005). "The Role of Protected Areas in Conserving Biodiversity and Sustaining Local Livelihoods." Annual Review of Environment and Resources 30(1): 219‐25
Thank you!
Protected areas* by category
DecadeIUCN Category
TotalIa Ib II III IVPrior to 1920 8 1 91920s 10 0 1 2 0 131930s 12 0 3 0 1 161940s 0 0 0 0 0 01950s 3 0 0 0 0 31960s 3 0 0 0 0 31970s 29 0 0 0 18 471980s 26 0 14 0 14 541990s 4 0 13 0 5 22After 2000 0 0 3 0 0 3Total 95 0 34 2 39 170*Only the ones that have been formally designated as such; categories V and VI have also been excluded from the analysis
Propensity Score Distribution (Forests)
Propensity Score Distribution (Mangroves)