Simulation And Application On The Sustainable Grasslands Model In The Meadow Area Of Qinghai-tibetan Plateau

Qinghai-Tibetan Plateau(QTP)is the largest and most extensive plateau in the world and is host to one of its largest pastoral ecosystems.This high plateau is the source for major Asian rivers,and it is a huge carbon sink and global weather regulator.The QTP is not only ecologically significant,but also the feed base for the grassland animal husbandry in China.The QTP is a crucial and fragile environment that's highly sensitive to climate change.Abundant evidence in the literature suggested that extensive areas of grasslands in the QTP have become degraded to a great extent.The potential causes for grassland degradation in QTP area have been identified as: unsustainable grazing management,global climate change,excessive herbivores,soil disturbance from small mammals,historical-cultural impediments,and population growth.Of these,overgrazing is undoubtedly regarded as one of the major causes of degradation.The sustainable development of the pastoral-animal husbandry in China is the crucial research area in pastoral science.The grazing system is complex,comprising many components.Each of these components has been studied in detail.The need for it to be integrated within the farming system in a profitable and sustainable way,limits the usefulness of relying solely on field experimentation to obtain answers.Modelling and simulation of complex farming systems provides the most efficient method of undertaking management and systems research to improve decision making.In order to capture the dynamic interactions between different components and maximise the long-term profitability of the grazing system.A bioeconomic model that will be able to adequately mimic the dynamic nature of pasture resources and simulate the sequential nature of the dynamic changes in grazing systems under climatic uncertainty in the alpine area of the QTP is proposed.Monte Carlo simulation procedures are used to evaluate a range of policies in managing pasturelands.This descriptive simulation framework is able to investigate the expected production outcomes,economic performance,household financial outcomes,and risks associated with pasture improvement technologies and stocking rate policies over a relatively long planning horizon.Five sub-models,namely soil,pasture growth,botanical composition,Tibetan sheep or yak production,and financial performance are encompassed in the current model.In the current model,an independent economic sub-model is constructed,with all the economic calculations executed after the biological simulation.The economic sub-model allows the running of multiple enterprises and is assumed to aim to maximise the present value of the annual cash flows over the planning horizon.Water run-off and wind erosion calculations in the soil sub-model are based on the functions proposed by previous scholars.In the pasture growth and botanical composition sub-models,to mimic the pasture composition change,the functional approach is adopted,and a relatively simple sigmoid pasture growth curve in combination with a growth index that combines light,temperature and moisture constraints,is applied in the model to mimic the growth rate and accumulative aboveground biomass.An empirical pasture composition sub-model which adapts and modifies the method proposed on the use of ‘partial' paddocks is developed.In the animal sub-model,the Australian ruminant feeding standard,which is also known as the CSIRO system,is used and in combination with an animal number model which is modified by mortality,reproduction,sales and purchases on a daily time-step,it is used to mimic the flock structure and dynamics across multiple age cohorts.The construction of the animal sub-model is mainly focused on the energy pathways and metabolism energy is used to evaluate the energy requirements of grazing ruminants and predict the production performance.Functions from the system are totally adopted with some parameters modified in order to better simulate the yak and Tibetan sheep.Parameterization and validations are implanted for the pasture growth and animal production sub-models and a case study in regard to the Oula Tibetan sheep production performance is carried out.Problems and the potential solutions for the sustainable development of the production system is discussed and conclusions are listed below.1.The CSIRO intake model could be implemented on the alpine rangeland in QTP area,the selective grazing simulation in the CSIRO system performs better on Tibetan sheep than that on the yak.Attention must be paid to the proportion of the 6 digestibility pools in both desirables and undesirables.A nominated DMD simulation is initially developed and added in order to overcome the sensitivity issues when implanting the selective grazing approach,as this allows the modeller to adjust and best represent the seasonal and monthly variation in DMD between desirables and undesirables,which influences the capacity of livestock selection to maximise energy intake on a daily time-step.2.This nominated DMD approach shows promising results in modelling the intake of grazing sheep in the alpine meadow area of the QTP.But this new approach lacks statistical validation for its veracity,therefore future development or validation for this new approach will be needed.Due to its complexity,the current intake model is not suitable for simple simulation model.3.The daily flock structures and dynamics could be mimicked by the discrete,age-structured animal number model,which is modified by mortality,reproduction,sales and purchases on a daily time-step,developed in the study.4.A simple sigmoid equation is adopted and improved in the current model,a growth index factor(between 0 to 1)is used as a coefficient in the sigmoid equation.The derived new ? for desirables and undesirables in the case study area are 0.076 and 0.077,respectively,new ? is 1.01 for both desirables and undesirables.5.Parameters in CSIRO system were validated by using the deterministic sensitivity analysis and least square method.Parameter CN1,CM2,CG8 for yak were revised as 0.0041,0.37,and 18.07,respectively.6.It's recommended to maintain the flock size number between 1.2 to 1.5 head/ha/year or 1.3 to 1.8 SE/ha/year in the case study area to maintain the long-term stability of pasture composition change as well as the economic return.