Explicit Representation of Grazing Activity in a Diagnostic Terrestrial Model: A Data‐Process Combined Scheme

Abstract

Grazing activity is a fundamental behavior in pasture ecosystems and, globally, is a major disturbance that leads to destruction of terrestrial biomass. However, its impact on ecosystem C sequestration at large scales is not well understood due to its obvious anthropogenic property. In this study, we proposed a Data‐Process combined Grazing Scheme (DPGS) to quantify the regional grazing impact on ecosystem C sequestration in the typical pasture ecosystem, Temperate Eurasian Steppe. First, a pixel‐based livestock distribution map was generated based on fine‐scale (province/prefecture) inventory data using a resource‐oriented livestock distribution approach. Then the C consumption due to grazing (Closs,graze) was simulated by combining a late version of a remote‐sensing‐based terrestrial model, the Boreal Ecosystem Productivity Simulator and the Shiyomi grazing model. The modeled regional livestock density was evaluated against the Gridded Livestock of the World data set. The DPGS was able to reproduce the spatial distribution of livestock. Because extralarge herbivores (camel and horse) were involved in the calculation, the DPGS predicts higher livestock density than the Gridded Livestock of the World data set over 70% of the region. The modeled Closs,graze and its seasonal variability were validated against multiple site‐based data sets. The results showed good agreements with the field observations of Closs,graze. With further tests and data incorporations, this scheme has the potential to produce high‐resolution data sets of livestock distribution and Closs,graze and become a useful diagnostic instrument for model evaluation, parameterization, and intercomparison.

Analyzing NPP Response of Different Rangeland Types to Climatic Parameters over Mongolia

“…Recently it has been applied and validated to monitor the dynamic changes in the productivity of various vegetation types, such as shrubland, farmland, and grassland ecosystems [52]. Accordingly, the model was used in mapping NPP spatial and temporal variations as a response to multiple distributors (e.g., forest fires, extreme climate events, drought, and climate change) at regional, continental, and global scales [50,[53][54][55][56][57] to quantify the water-use efficiency in dryland ecosystems [58], and to assess the grazing impact on ecosystem carbon sequestration [59].…”

Movement drives population dynamics of one of the most mobile ungulates on Earth: Insights from a mechanistic model

“…In addition, the mechanistic, ecophysiological nature of our herbivore–vegetation model allows one to alter process representations according to different ecological hypotheses, making it ideal for examining the implications of competing hypotheses or for gaining mechanistic understanding of the processes at work. While herbivores have been added to DGVMs (Chang et al, 2013; Chen et al, 2019; Luo et al, 2012; Pachzelt et al, 2013; Zhu et al, 2018), to our knowledge, moving herbivores have not. We therefore incorporated moving large herbivores into the DGVM Lund‐Potsdam‐Jena General Ecosystem Simulator (LPJ‐GUESS) to test two hypotheses: long‐distance movements (1) lead to an increase in the abundance of herbivores and (2) stabilize population dynamics.…”