Using seasonal stochastic dynamic programming to identify optimal management decisions that achieve maximum economic sustainable yields from grasslands under climate risk

Karl Behrendt, Oscar Cacho, James M Scott, Randall Jones

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6 Citations (Scopus)

Abstract

There are significant challenges in managing the trade-offs between the production of pastures and grazing livestockfor profit in the short term, and the persistence of the pasture resource in the longer term under stochasticclimatic conditions. The profitability of using technologies such as grazing management, fertiliser inputs and therenovation of pastures are all influenced by complex inter-temporal relations that need to be considered to providesuitable information for managers to enhance tactical and strategic decision making.In this study pasture is viewed as an exploitable renewable resourcewith its state defined by total pasture quantityand the proportion of desirable species in the sward. The decision problem was formulated as a stochasticdynamic programming (SDP) model where the decision variables are seasonal stocking rate and pasture resowingand the objective is to maximise the present value of future economic returns. The solution defines theoptimal seasonal decisions for all intervening states of the system as uncertainty unfolds.The model was applied to a representative farm in the high rainfall temperate pasture zone of Australia and thepasture states underwhich tactical grazing rest, lowstocking rates and pasture re-sowing are optimal were identified.Results provide useful general insights as well as specific prescriptions for the case study farm. The frameworkdeveloped in this paper provides a means of identifying optimal tactical and strategic decisions that achievemaximum sustainable economic yields from grazing systems.
Original languageEnglish
Pages (from-to)13-23
Number of pages11
JournalAgricultural Systems
Volume145
DOIs
Publication statusPublished - 2016

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dynamic programming
grasslands
pastures
climate
economics
grazing
farms
grazing management
sward
stocking rate
profitability
profits and margins
decision making
managers
uncertainty
sowing
fertilizers
case studies
rain

Cite this

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title = "Using seasonal stochastic dynamic programming to identify optimal management decisions that achieve maximum economic sustainable yields from grasslands under climate risk",
abstract = "There are significant challenges in managing the trade-offs between the production of pastures and grazing livestockfor profit in the short term, and the persistence of the pasture resource in the longer term under stochasticclimatic conditions. The profitability of using technologies such as grazing management, fertiliser inputs and therenovation of pastures are all influenced by complex inter-temporal relations that need to be considered to providesuitable information for managers to enhance tactical and strategic decision making.In this study pasture is viewed as an exploitable renewable resourcewith its state defined by total pasture quantityand the proportion of desirable species in the sward. The decision problem was formulated as a stochasticdynamic programming (SDP) model where the decision variables are seasonal stocking rate and pasture resowingand the objective is to maximise the present value of future economic returns. The solution defines theoptimal seasonal decisions for all intervening states of the system as uncertainty unfolds.The model was applied to a representative farm in the high rainfall temperate pasture zone of Australia and thepasture states underwhich tactical grazing rest, lowstocking rates and pasture re-sowing are optimal were identified.Results provide useful general insights as well as specific prescriptions for the case study farm. The frameworkdeveloped in this paper provides a means of identifying optimal tactical and strategic decisions that achievemaximum sustainable economic yields from grazing systems.",
keywords = "Grazing SystemsStocking Rate, Pasture renovation",
author = "Karl Behrendt and Oscar Cacho and Scott, {James M} and Randall Jones",
note = "Imported on 12 Apr 2017 - DigiTool details were: Journal title (773t) = Agricultural Systems. ISSNs: 0308-521X;",
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N2 - There are significant challenges in managing the trade-offs between the production of pastures and grazing livestockfor profit in the short term, and the persistence of the pasture resource in the longer term under stochasticclimatic conditions. The profitability of using technologies such as grazing management, fertiliser inputs and therenovation of pastures are all influenced by complex inter-temporal relations that need to be considered to providesuitable information for managers to enhance tactical and strategic decision making.In this study pasture is viewed as an exploitable renewable resourcewith its state defined by total pasture quantityand the proportion of desirable species in the sward. The decision problem was formulated as a stochasticdynamic programming (SDP) model where the decision variables are seasonal stocking rate and pasture resowingand the objective is to maximise the present value of future economic returns. The solution defines theoptimal seasonal decisions for all intervening states of the system as uncertainty unfolds.The model was applied to a representative farm in the high rainfall temperate pasture zone of Australia and thepasture states underwhich tactical grazing rest, lowstocking rates and pasture re-sowing are optimal were identified.Results provide useful general insights as well as specific prescriptions for the case study farm. The frameworkdeveloped in this paper provides a means of identifying optimal tactical and strategic decisions that achievemaximum sustainable economic yields from grazing systems.

AB - There are significant challenges in managing the trade-offs between the production of pastures and grazing livestockfor profit in the short term, and the persistence of the pasture resource in the longer term under stochasticclimatic conditions. The profitability of using technologies such as grazing management, fertiliser inputs and therenovation of pastures are all influenced by complex inter-temporal relations that need to be considered to providesuitable information for managers to enhance tactical and strategic decision making.In this study pasture is viewed as an exploitable renewable resourcewith its state defined by total pasture quantityand the proportion of desirable species in the sward. The decision problem was formulated as a stochasticdynamic programming (SDP) model where the decision variables are seasonal stocking rate and pasture resowingand the objective is to maximise the present value of future economic returns. The solution defines theoptimal seasonal decisions for all intervening states of the system as uncertainty unfolds.The model was applied to a representative farm in the high rainfall temperate pasture zone of Australia and thepasture states underwhich tactical grazing rest, lowstocking rates and pasture re-sowing are optimal were identified.Results provide useful general insights as well as specific prescriptions for the case study farm. The frameworkdeveloped in this paper provides a means of identifying optimal tactical and strategic decisions that achievemaximum sustainable economic yields from grazing systems.

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