Optimization of landscape spatial structure aiming at achieving carbon neutrality in desert and mining areas

Guo, Hongqiong; Yu, Qiang; Pei, Yong; Wang, Ge; Yue, Depeng

doi:10.1016/j.jclepro.2021.129156

Cited by 50 publications

(38 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In particular, Node 27 had only one neighboring node, Node 26, and we optimized it by adding neighboring nodes. We built ecological corridors between Node There have been many studies on the optimization of ecospatial networks, and most of them were based on landscape risk or network stability [20][21][22]. Compared with other studies, the average clustering coefficient of the vegetation ecospatial network constructed in this study is larger and the network structure is relatively more stable.…”

Section: Suggestions For Optimizing the Vegetation Ecospatial Network In The Yrbmentioning

confidence: 90%

“…These indicators are divided into those used to evaluate the topological characteristics of ecological nodes and those used to evaluate the ecospatial network as a whole. Combining the ecological significance of each topological indicator and the selection of topological indicators in other studies of ecospatial networks, we selected 10 topological indicators to evaluate the ecospatial network of the Yellow River Basin [21,40]. Among them, six topological indicators were used to evaluate the ecological nodes, and four topological indicators were used to evaluate the network as a whole (Table 2).…”

Section: Algorithm For Topological Indicatorsmentioning

confidence: 99%

“…In this study, we found the relationship between the topological characteristics of vegetation and its carbon sequestration capacity, which implies that the spatial pattern described by the ecospatial network is connected with vegetation physiological processes. In addition, a previous study constructed the ecospatial network of Erdos and converted the vegetation carbon sequestration capacity according to the area of vegetation [21]. This has some significance in large-scale studies but may not be fully compatible with reality.…”

Section: Prospects and Limitations Of This Studymentioning

confidence: 99%

“…Complex network theory has been widely applied in ecology [19]. In studies related to landscape ecology, researchers often use an algorithm of complex networks to construct networks composed of vegetation or other types of landscape patches, which are called ecospatial networks or ecological networks [20,21]. In addition, the construction method of ecospatial networks is very mature, mainly achieved by using various remote sensing data and MCR models [22].…”

Section: Introductionmentioning

confidence: 99%

“…These ecological problems not only damage the human living environment, but also affect the growth of vegetation. Vegetation is considered to be the best carrier of carbon capture and sequestration, and the ecological problems that the Yellow River Basin is facing have a negative effect on the realization of carbon neutrality [21]. Meanwhile, the Yellow River Basin is a key area for the construction of future national ecological projects.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Study on the Relationship between Topological Characteristics of Vegetation Ecospatial Network and Carbon Sequestration Capacity in the Yellow River Basin, China

Fang

et al. 2021

Remote Sensing

Self Cite

View full text Add to dashboard Cite

Achieving carbon neutrality is a necessary effort to rid humanity of a catastrophic climate and is a goal for China in the future. Ecological space plays an important role in the realization of carbon neutrality, but the relationship between the structure of vegetation ecological space and vegetation carbon sequestration capacity has been the focus of research. In this study, we extracted the base data from MODIS products and other remote sensing products, and then combined them with the MCR model to construct a vegetation ecospatial network in the Yellow River Basin in 2018. Afterward, we calculated the topological indicators of ecological nodes in the network and analyzed the relationship between the carbon sequestration capacity (net biome productivity) of ecological nodes and these topological indicators in combination with the Biome-BGC model. The results showed that there was a negative linear correlation between the betweenness centrality of forest nodes and their carbon sequestration capacity in the Yellow River Basin (p < 0.05, R2 = 0.59). On the other hand, there was a positive linear correlation between the clustering coefficient of grassland nodes and their carbon sequestration capacity (p < 0.01, R2 = 0.49). In addition, we briefly evaluated the vegetation ecospatial network in the Yellow River BASIN and suggested its optimization direction under the background of carbon neutrality in the future. Increasing the carbon sequestration capacity of vegetation through the construction of national ecological projects is one of the ways to achieve carbon neutrality, and this study provides a reference for the planning of future national ecological projects in the Yellow River Basin. Furthermore, this is also a case study of the application of remote sensing in vegetation carbon budgeting.

show abstract

Section: Suggestions For Optimizing the Vegetation Ecospatial Network In The Yrbmentioning

confidence: 90%

Section: Algorithm For Topological Indicatorsmentioning

confidence: 99%

Section: Prospects and Limitations Of This Studymentioning

confidence: 99%