Estimating the Costs, Capacity (Supply), and Tradeoffs of Ecosystem Services in a Resource Assessment

Transcription

1 Estimating the Costs, Capacity (Supply), and Tradeoffs of Ecosystem Services in a Resource Assessment R. Bernknopf University of New Mexico S. Faulkner USGS Leetown Science Center B. Chivoiu USGS National Wetlands Research Center ACES December 12, 2012

2 Key Policy Questions What are the ecosystem effects from likely terrestrial carbon sequestration management actions? How do we incorporate social and economic sciences that enhance our ability to quantitatively evaluate the full range of effects of proposed terrestrial carbon sequestration strategies? How does it affect the benefits B = P DQ of the policy? ( )

3 Motivation for research There are many analyses about the economic uncertainty of values for ecosystem services that is reflected in the price or nonmarket value. Few, if any estimates of the effect of uncertainty of the quantity of ecosystem services? Reliability of the policy - Do we get all the benefits from a management activity that analysis tells we should? Objective is to maximize benefits and minimize uncertainty simultaneously

4 Policy/Management strategies and ecosystem services approach Mitigation Actions: Land Use/ Cover Management Ecosystem Structure, Processes and Function Ecosystem Goods and Services Ecological evaluation Quantitative Spatially Explicit Metrics + Economic evaluation Policy Portfolios and Mitigation Options Portfolio Analysis Valuation Benefits / Costs

5 Spider diagram of management scenarios for five ecosystem services Carbon Sequestration Sediment Retention 0.00 Waterfowl Baseline Targeted Reforestation Max Eucalyptus Water Supply Nitrate

6 Policy scenarios and benefits A policy scenario i, i=1,,n scenarios is composed of a land portfolio in a region of k, k=1,,k land units of land uses that produces market commodities Vi and ecosystem services benefits B ( i Z). For any scenario i there is a regional land grid of available agricultural lands that, if converted to forest in a scenario, has annualized net value of benefits B i. A policy is weighted by the emphasis placed on the types of services provisioned. B i K å k=1 ( Z) = bz ( ) k, i = 1,..., N

7 Research approach A land use / land cover (LULC) portfolio analysis of an afforestation policy that maximizes the production of ecosystem services (expected return on investment (ROI)) and minimizes the standard deviation (risk) of the quantity of ecosystem services produced given their values. r = B t - B 0 B 0 s = N N åå i=2 i=2 B i B j s i s j

8 Multiobjective Optimization Two objectives are to maximize B and minimize risk σ, which can be converted to a single objective to minimize the relative risk coefficient of variation: Min CV ( B) N s.t. B i ³ B 0 where CV = s N r N

9 Expected return vs. standard deviation r N B 1 B* B i Lower limit benefit constraint B 2 B 0 0 s N

10 Carbon Management Strategy - Increase biological carbon sequestration on the landscape to mitigate increasing CO2/climate change effects Scenario 1: Baseline no change in current land cover (forest, agriculture, restored forested wetlands) Scenario 2: Convert agriculture to forest through targeted afforestation by selecting specific landscape locations - hydric soils, soybean production, low elevation - high hydrologic connectivity score - watersheds with currently high sediment and nutrient loads - near watershed outlet - native Quercus/Carya species - increase current forest area by 15% over 20 years

11 Carbon Management Strategy - Increase biological carbon sequestration on the landscape to mitigate increasing CO2/climate change effects Scenario 3: Convert agriculture to forest through random afforestation - fast growing Eucalyptus species - increase current forest area by 15% over 20 years - harvest every 10 years (biomass energy) Scenario 4: Convert all agriculture to Eucalyptus forest through random afforestation Two Parishes in LA Madison and Tensas

12 Current Practice in MAV: random conversion of cropland to forests

13 Targeting afforestation to enhance other ecosystem services Connector Source Sink

14 Prices and quantities for ecosystem services Scenario Baseline Eucalyptus (15%) Targeted reforestation (15%) Eucalyptus (max) P(carbon) 1 $10.09 $10.09 $10.09 $10.09 P(waterfowl) 2 $7.90 $7.90 $7.90 $7.90 P(Water quality nitrate) 3 $ $ $ $ P(Water quality sediment) 4 $2.76 $2.76 $2.76 $2.76 P(Water quantity) 5 $ $ $ $ Q (carbon) mg/ha Q (waterfowl) in , , , ,876.1 Q(Water quality nitrate) kg/ha Q(Water quality sediment) metric tons 12,851 12,426 7,253 4,908 Q(Water annual flow) m 3 /s 2,133 2,096 1,997 1,614 1 California cap and trade market Gascoigne et al Jenkins et al Hansen and Ribaudo delivery cost price for a ft 3

15 Forest establishment and maintenance costs Land prices: Madison Parish - $1,675/ha - $4,586/ha Tensas Parish - $4,700/ha - $7,384/ha Hectares converted to forest 9,632 (15%); 86,747 (MAX) Total hectares 167,745 ha Afforestation activity Establishment costs/ha ($2009) Establishment and maintenance costs/ha ($2009) Eucalyptus Land preparation 252 Weed control 264 Plantation establishment 112 Seedlings 416 Hardwood Land preparation 145 Saplings and planting 209 Supervision 109 Fertilization 151 Fire and safety 2 Weed control 142 Weed control 72 Boundary 8 Management 32 Gonzalez et 2011 Zhu et al 2010

16 Ecosystem service expected return and standard deviation Scenario Baseline Eucalyptus (15%) Targeted reforestation (15%) Eucalyptus (max) r(carbon) r(waterfowl) r(water quality nitrate) r(water quality sediment) r(water quantity) σ(carbon) σ(waterfowl) 16,923,356 16,630,274 17,668,619 17,509,519 σ(water quality nitrate) σ(water quality sediment) 14,478 14,413 7,599 5,503 σ(water quantity) 2,888 2,834 2,581 2,161

17 Management scenario return, uncertainty, and coefficient of variation Scenario CV Eucalyptus (15%) B ,707 2,435,350 Targeted reforestation (15%) B , ,256 Eucalyptus (max) B ,998 36,362 r s

18 Summary We have integrated natural and economic sciences in a multiobjective optimization analysis to better understand the impacts and tradeoffs involved in comparing reforestation management scenarios with different objectives in a risk return analytical framework. From our analysis the targeted hardwood scenario has a lower coefficient of variation that indicates it is a better management option.