EXISTENCE OF UNIQUE LIMITING PROBABILITY VECTORS IN STOCHASTIC PROCESSES WITH MULTIPLE TRANSITION MATRICES

Concepts associated with stochastic process containing multiple transition matricies are discussed. It is proved that under certain conditions, a process with m transition matrices has m unique limiting probability vectors. This result extends the notion of discrete Markov processes to problems with intrayear and interyear dynamics. An example using a large DP model illustrates the usefulness of the concepts developed to applied problems.Research Methods/ Statistical Methods,

Optimal ranch management strategies with stochastic sequential decision models

Typescript (photocopy).The profitability of ranch operations are largely dependent on stochastic prices and range conditions. These variables are stochastic, but not entirely beyond the influence of ranchers. Current management decisions will impact range conditions and prices received for livestock in the future. These characteristics necessitate the application of stochastic sequential modeling techniques for empirical analysis of management alternatives. This study utilized discrete stochastic and dynamic programming to determine decision rules for two range livestock applications. The first application is concerned with the timing of range improvements on Macartney rose infested rangeland. Roller chopping followed by burning is an effective method of improving Macartney rose on rangeland. However, uncertainty associated with implementing effective burns adversely affects economic feasibility of the treatment sequence. Discrete stochastic programming is used to determine optimal burning schedules under uncertainty. These schedules and expected net returns vary with changes in the probability of a successful burn. Generally, as the probability of a successful burn increases the frequency of burning decreases and net returns increase. The second application addresses the marketing of weaned calves as a method of improving the efficiency of forage utilization. Many of the problems encountered in ranching stem from the uncertainty associated with forage availability and the relatively stable forage requirements of the traditional cow-calf operation. This results in under utilization during forage surpluses and costly over utilization during shortages. Smaller cow herds combined with opportunistic wintering and possible carrying over of calves to the following fall would allow forage requirements to be manipulated in response to forage availability. Dynamic programming results suggest that the smaller cow-calf-yearling operation has potential to increase returns over a cow-calf operation. Decomposition of these results indicates that a smaller herd increases returns under a wide range of initial price and range conditions. The opportunity to market calves as yearlings is advantageous under all initial conditions

Optimal ranch management strategies with stochastic sequential decision models

Typescript (photocopy).The profitability of ranch operations are largely dependent on stochastic prices and range conditions. These variables are stochastic, but not entirely beyond the influence of ranchers. Current management decisions will impact range conditions and prices received for livestock in the future. These characteristics necessitate the application of stochastic sequential modeling techniques for empirical analysis of management alternatives. This study utilized discrete stochastic and dynamic programming to determine decision rules for two range livestock applications. The first application is concerned with the timing of range improvements on Macartney rose infested rangeland. Roller chopping followed by burning is an effective method of improving Macartney rose on rangeland. However, uncertainty associated with implementing effective burns adversely affects economic feasibility of the treatment sequence. Discrete stochastic programming is used to determine optimal burning schedules under uncertainty. These schedules and expected net returns vary with changes in the probability of a successful burn. Generally, as the probability of a successful burn increases the frequency of burning decreases and net returns increase. The second application addresses the marketing of weaned calves as a method of improving the efficiency of forage utilization. Many of the problems encountered in ranching stem from the uncertainty associated with forage availability and the relatively stable forage requirements of the traditional cow-calf operation. This results in under utilization during forage surpluses and costly over utilization during shortages. Smaller cow herds combined with opportunistic wintering and possible carrying over of calves to the following fall would allow forage requirements to be manipulated in response to forage availability. Dynamic programming results suggest that the smaller cow-calf-yearling operation has potential to increase returns over a cow-calf operation. Decomposition of these results indicates that a smaller herd increases returns under a wide range of initial price and range conditions. The opportunity to market calves as yearlings is advantageous under all initial conditions

A DISCRETE STOCHASTIC PROGRAMMING MODEL TO ESTIMATE OPTIMAL BURNING SCHEDULES ON RANGELAND

McCartney rose is a range management problem on 500,000 acres of rangeland in Texas. Roller chopping followed by burning is an effective method of improving infested rangeland. However, uncertainty associated with implementing effective burns adversely affects economic feasibility of the treatment sequence. Discrete stochastic programming is used to determine optimal burning schedules under uncertainty. Optimal schedules and expected net returns vary with changes in the probability of a successful burn

EXISTENCE OF UNIQUE LIMITING PROBABILITY VECTORS IN STOCHASTIC PROCESSES WITH MULTIPLE TRANSITION MATRICES

Concepts associated with stochastic process containing multiple transition matricies are discussed. It is proved that under certain conditions, a process with m transition matrices has m unique limiting probability vectors. This result extends the notion of discrete Markov processes to problems with intrayear and interyear dynamics. An example using a large DP model illustrates the usefulness of the concepts developed to applied problems

Communing with Nature: The Collective Journey of Yatoo Artists and its Pedagogical Potentials

Increasing concern over environmental sustainability and socioecological well-being has motivated people to consider ways to reconnect humans with the natural world through lifestyle changes that integrate well with natural systems. Educators who share environmental concerns have explored diverse aspects of ecological art practices to envision an extended and socially relevant role of art. Accordingly, the present study aims to bring educators' attention to a collective journey of artists who have immersed themselves in making an affective relationships with nature. Regarding the journey as an invaluable cultural resource that holds the potential to extend the horizon of how we may live with nature, it examines the collective journey of the artists in Yatoo, an artist association based in Gongju, a greenery city in the southwest region of South Korea. The guiding questions set for the contextual analysis are: 'how do Yatoo artists become native to their place?' and 'what can be learned from their collective journey?'. First, the collective journey of the artists is examined based on four major factors: regionality, positioning, methodology and networking. This is followed by discussions focusing on the value of the collective identity shaped by bioregionally conscious art practices and the pedagogical potentials arising from the collective journey. This paper suggests that the collective journey of Yatoo's life-sustaining practice, operating in an era of environmental crisis, contributes to the recently developing alternative pedagogical discussions by opening up dialogues that navigate ways to encourage more sustainable practices for the future