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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Accurate estimation of livestock carrying capacity (LCC) and implementation of an appropriate actual stocking rate (ASR) are key to the sustainable management of grazing adapted alpine grassland ecosystems. The reliable determination of aboveground biomass is fundamental to these determinations. Peak aboveground biomass (AGBP) captured from satellite data at the peak of the growing season (POS) is widely used as a proxy for annual aboveground biomass (AGBA) to estimate LCC of grasslands. Here, we demonstrate the limitations of this approach and highlight the ability of POS in the estimation of ASR. We develop and trail new approaches that incorporate remote sensing phenology timings of grassland response to grazing activity, considering relations between biomass growth and consumption dynamics, in an effort to support more accurate and reliable estimation of LCC and ASR. The results show that based on averaged values from large-scale studies of alpine grassland on the Qinghai-Tibet Plateau (QTP), differences between AGBP and AGBA underestimate LCC by about 31%. The findings from a smaller-scale study that incorporate phenology timings into the estimation of annual aboveground biomass reveal that summer pastures in Haibei alpine meadows were overgrazed by 11.5% during the study period from 2000 to 2005. The methods proposed can be extended to map grassland grazing pressure by predicting the LCC and tracking the ASR, thereby improving sustainable resource use in alpine grasslands.

Details

Title
An Improved Approach to Estimate Stocking Rate and Carrying Capacity Based on Remotely Sensed Phenology Timings
Author
Shi, Yan 1   VIAFID ORCID Logo  ; Brierley, Gary 2 ; Perry, George L W 2 ; Gao, Jay 2 ; Li, Xilai 3 ; Prishchepov, Alexander V 4   VIAFID ORCID Logo  ; Li, Jiexia 5 ; Han, Meiqin 6 

 State Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China; School of Environment, The University of Auckland, Auckland 1010, New Zealand; [email protected] (G.B.); [email protected] (G.L.W.P.); [email protected] (J.G.) 
 School of Environment, The University of Auckland, Auckland 1010, New Zealand; [email protected] (G.B.); [email protected] (G.L.W.P.); [email protected] (J.G.) 
 State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China; [email protected] 
 Department of Geosciences and Natural Resource Management (IGN), University of Copenhagen, 1350 Copenhagen, Denmark; [email protected] 
 Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810008, China; [email protected] 
 College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China; [email protected] 
First page
1991
Publication year
2024
Publication date
2024
Publisher
MDPI AG
e-ISSN
20724292
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3067436110
Copyright
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.