Trade-offs between Agricultural Production and Ecosystem Services at a

Farm Level

by

Seth Somana & Steven Kraftb

a. Dickinson State University b. Southern Illinois University Carbondale

Overview of Presentation

Introduction

Research Objective

Study Area

Methodology

Results

Conclusion

Multifunctionality

Multifunctionality refers to the possibility that an economic activity may have multiple outputs, both commodity and non-commodity outputs and consequently may contribute to several societal objectives at once.

Example in agriculture:

positive externality (open space, landscape amenities);

negative externality (soil erosion, eutrophication)

Agricultural landscapes with riparian buffers have positive multifunctional attributes (Boody et al., 2005, Jordan et al., 2007).

Riparian Buffers provide a variety of ecosystem services

Enhance Water Quality

Provide Terrestrial Habitat

Provide Stream Habitat

Flood Control

Carbon Sequestration

Agriculture contribute to 50% of the land in the contiguous U.S (Vitousek 1997) most of these lands are privately owned.

Multiple attributes or joint products of riparian buffers have received considerable attention in the policy realm.

Problem : Public goods

Economic or monetary valuation of ecosystem services is difficult due to:

Non availability of a functioning market

Not all services have a market price (e.g. photosynthesis)

Services are interrelated

Time consuming

High Cost

The U.S. government has made available a number of federal programs to provide markets for these ecosystem services by properly managing the activities within an agricultural watershed.-- Conservation Compliance, Land retirement program, Working land

NCBI formed in 1997 is a public and private partnership aimed at helping farmers and landowners install conservation buffer on their lands (USDA-ERS 2000).

The Goal of NCBI--- install 2 million miles of buffer on environmentally sensitive lands.

By the year 2000 one million miles was installed; 2004 1.55 million miles.

Conservation Policies

A large number of factors affect land owners’ willingness to change land use decisions to capture or maintain environmental benefits (Lockeretz, 1990; Napier, 1991; Kraft and Loftus, 2003)

Personal characteristics of the farm owner (age, education)

Institutional connection

Economic factors

Financial incentives

Legal rights

Decision Environment

1. Develop a methodology to capture the various ecosystem services provided by riparian buffers and agricultural production on a farm level.

2. How much of these services should be produced in a socially efficient way on a farm level?

Research Purpose and Questions

-How much of commodity and non-commodity outputs that could be produced?

3. Develop a trade off between commodity and non-commodity outputs.

Ecosystem Services

Gro

ss

Ma

rgin

Production possibilities curve

Agricultural income is more important

Environmental quality is more important.

Environmental quality and agricultural income are equally important.

Evaluating the trade-offs among multiple objectives

Cache Watershed encompasses, 1,944km2 of southern Illinois near the confluence of the Mississippi and Ohio Rivers. The Watershed has diverse ecological resources and unique natural communities. At least 100 state threatened or endangered plant and animal species are known within the watershed (USFWS 1990).

Endangered species: Cypress and Tupelo swamps

Study Area

The Big Creek is a tributary of the Lower Cache River with a drainage area of 33,088 acres (51.7 square miles). This stream originates in Union County in the Lesser Shawnee Hills

Loss and fragmentation of natural habitat

Dramatically altered hydrologic systems

Sediment deposition in the wetlands

Land use and economic activities that are incompatible with the long term maintenance of ecological function

PROBLEMS ADDRESSED

Methodology

Integrated Modeling approach

Modeling based integrative decision making will be the methodology that will be used in this study.

Ecosystem services-Water quality: reduced sediment, N, and P loadsWildlife enhancement.

Economic: Gross margin

Economic model

Optimization

model

EA

Water QualityIndex

AGNPS

IDENTIFY THE TRADE OFF CURVE THAT MAXIMIZES GROSS MARGIN & ESS

Generates the LU pattern

GIS Platform

Wildlife IndexE

cosystem services

Input-output

Ecosystem Services• Sediment Reduction• Nitrogen Reduction• Phosphorous Reduction• Wildlife Enhancement

Modeling Framework

Evolutionary Algorithms (EAs)

Simplified models of biological evolution, implementing the principles of Darwinian theory of natural selection (“survival of the fittest”) and genetics

Stochastic search and optimization algorithms

Key idea: computer simulated evolution as a problem-solving technique

Integer Code Binary Code Landuse & Management Acronym

0 0000 Riparian buffers RIP

1 0001 Alfalfa Hay ALF

2 0010 Corn no-till CNT

3 0011 Corn conservation till Fall CVF

4 0100 Corn conservation till Spring CVS

5 0101 Double crop conventional wheat DVW

6 0110 Conservation Reserve Program (CRP) PCR

7 0111 Soybean no-till SNT

8 1000 Soybean conventional till fall SVF

9 1001 Soybean conventional till spring SVS

10 1010 Double crop no-till soybean DNS

11 1011 Double crop no-till DNT

12 1100 Wheat conventional tillage WNB

13 1101 Wheat no-till WNT

14 1110 Grasslands GLM

15 1111 Riparian buffers RIP

Landuse and management choicesNumber of landuse and management types: 14Gene: Binary string of length 4

Multi-objective optimization (MOO):

To find a large number of Pareto optimal solutions with respect to multiple objective functions.

Pareto Optimal Solutions

Multi-objective Optimization ProblemMulti-objective Optimization Problem))(...,),(),(()( 21 xxxxf kfffMaximize

Xxsubject to

Max

imiz

e

Maximize)(1 xf

Many Pareto-optimal solutions

)(2 xf

Goal of MOO1. Find solutions close to Pareto optimum2. Find as many diverse solutions as possible

Agricultural Non-Point Source (AGNPS) Pollution Model –

USDA lead agency

AGNPS single event, empirical based distributed parameter model

AGNPS operates on a cell basis

AGNPS requires 22 input parameters

To simulate riparian buffer -- Curve number (mixed deciduous forest); Manning’s n : 0.005;

C factor (95% vegetative density & 75% canopy cover);

Surface condition factor of 1.0

Water Quality Hydrological Model

Economic Model

Farm Economic Model based on Soil specific Crop yields Market Price Labor and Machinery Constraints Production (operating) costs

Wildlife Index model

USDA- NRCSLanduse typeTillage typeDistance to streams or water bodyDistance from forested areas

Data

Digitized Fields for the Big creek watershed

Soils- SSURGO

DEM

Price of crops, yields for various crops based on soil types

Cost of Production

Labor and machinery cost on a per farm basis

Nitrogen and Phosphorous application rate

Buffer width = 20ft + (1.5 x (for each 1% increase in slope)

Variable Buffer Width

5.7% of the watershed area (1055 acres)

Wildlife Index

Distance from streamDistance from forestCrop type Tillage typeWidth of buffer

Economic ModelSoil Specific Crop yields Cost of production and Market Price

Field-Farm-Cell lookups

--to capture the water quality parameters

Population 100Generation: 100Cross over probability: 0.5Mutation probability : 0.2

---- time: approximately 16 hrs

Results Integrated Modeling approach

0

0.2

0.4

0.6

0.8

1

1.2

-1000 -500 0 500 1000 1500 2000 2500

GM

0

0.2

0.4

0.6

0.8

1

-500 0 500 1000 1500 2000 2500

GM

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 500 1000 1500 2000 2500

GM

0

0.2

0.4

0.6

0.8

1

1.2

-500 0 500 1000 1500 2000 2500

GM

I st Gen 25 th Gen

50 th Gen 100 th Gen

Progression of GA

Results

Economic profit and Water quality

Results

20000

28000

36000

44000

52000

60000

68000

76000

20000 25000 30000 35000 40000

Wildlife Index

Gro

ss

Ma

rgin

($

)

A

B

C

Economic Profit and Wildlife Index

  Water quality Vs

Gross margin

Wildlife index Vs

Gross margin

Water quality Vs

Wildlife index

  Competitive Complementary Competitive Complementary Competitive Complementary

No ofFarms

68 23 91 0 58 33

Types of PPF relationships

Complementary relation betweengross margin and water quality.

Alfalfa (tons/acre) Complementary 2.8695    

Competitive2.9169 89 .760 -.306

Corn (bu/acre) Complementary 107.5450      

Competitive121.3445 89 .000 -4.244

Soybean (bu/acre) Complementary 32.3470      

Competitive38.7207 89 .000 -6.151

Wheat (bu/acre) Complementary 41.2305      

Competitive47.5531 89 .000 -5.435

Area (acres) Complementary 97.0597      

Competitive262.7512 89 .000 -6.484

Slope (percent) Complementary 8.5502      

Competitive7.5348

89 .0092.688

Agent type

  

VARIABLES Mean dfP-value t-value

89 3.71 0.899

--Small farms, on highly sloped areas with low crop productivity havea complementary relationship between gross margin and water quality

Summary of Analysis of tradeoffs done for high price scenario

It was costly to provide more ecosystem services as the price ofcommodity increased.

Most of the profit maximizers and conservationist was closer to the PPF – indication of efficiency.

With high price scenario all the farm had a competitive relationship indicating that with high prices it is economically profitable to have commodity crops.

Watershed scale Analysis

 Landuse Acres

 Maximizes

Gross margin

 Maximize

Water quality

 Maximize

Wildlife Index

Corn No-till 1,399.06 0.0 0.0

Corn Conservation Till 2,204.86 0.0 0.0

Soybean No Till 2,695.25 0.0 0.0

Soybean Conservation Till 2,744.51 0.0 0.0

Wheat 5,54.48 0.0 0.0

Double Crop 1,049.00 0.0 0.0

Alfalfa Hay 5,860.10 7,940.74 953.91

CRP 1,473.00 5,114.77 14,189.65

Pasture Grasslands 383.00 4,496.09 2,413

Buffer 77.00 890.00 885.00

Associated Landuse

Conclusion

In this study an integrated modeling approach (IMA) was developed that can be utilized by various decision makers in analyzing or designing policies that involve multifunctional agricultural outputs.

The study demonstrated that the IMA could be effectively used to find patterns of landuse and determine management choices that approximately optimize sets of economic and environmental objectives.

The IMA generates PPF for ecosystem service production and agricultural production at the farm level.

The IMA also shows that the PPF between water quality and gross margin can be complementary

With higher commodity prices more of an incentive is required in the form of governmental payment/incentives and cost share to promote environmental conservation.

Limitations

AGNPS as an yearly average even though AGNPS calculate the water quality for a single event rainfall rather than on an yearly basis.

Acknowledgements :

Kanpur genetic algorithm lab(Debb): NSGA-II source code

Questions

Contact: Seth Soman

email: soman.sethuram@dsu.nodak.edu