ECOLOGICAL NETWORKS IN AGROECOSYSTEMS: APPROACHES AND APPLICATIONS

doi:10.15302/J-FASE-2022466

Front. Agr. Sci. Eng.

2022, Vol. 9

Issue (4) : 523-535 https://doi.org/10.15302/J-FASE-2022466

REVIEW

ECOLOGICAL NETWORKS IN AGROECOSYSTEMS: APPROACHES AND APPLICATIONS

Ying GONG, Langqin YU, Lei ZHAO(

)

Beijing Key Laboratory of Biodiversity and Organic Farming, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China

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Abstract

● Agricultural intensification reduced the complexity and connectance of soil food webs.

● Agricultural intensification impaired the robustness of pollination networks.

● High connectance in co-occurrence networks indicates efficient nutrient utilization.

Complex network theory has been increasingly used in various research areas, including agroecosystems. This paper summarizes the basic concepts and approaches commonly used in complex network theory, and then reviews recent studies on the applications in agroecosystems of three types of common ecological networks, i.e., food webs, pollination networks and microbial co-occurrence networks. In general, agricultural intensification is considered to be a key driver of the change of agroecosystems. It causes the simplification of landscape, leads to the loss of biocontrol through cascading effect in food webs, and also reduces the complexity and connectance of soil food webs. For pollination networks, agricultural intensification impaired the robustness by reducing specialization and enhancing generality. The microbial co-occurrence networks with high connectance and low modularity generally corresponded to high efficiency in utilization of nutrients, and high resistance to crop pathogens. This review aims to show the readers the advances of ecological networks in agroecosystems and inspire the researchers to conduct their studies in a new network perspective.

Keywords bipartite network co-occurrence network food web network theory

Corresponding Author(s): Lei ZHAO

Just Accepted Date: 09 September 2022 Online First Date: 27 September 2022 Issue Date: 07 November 2022

Cite this article:

Ying GONG,Langqin YU,Lei ZHAO. ECOLOGICAL NETWORKS IN AGROECOSYSTEMS: APPROACHES AND APPLICATIONS[J]. Front. Agr. Sci. Eng. , 2022, 9(4): 523-535.

URL:

https://academic.hep.com.cn/fase/EN/10.15302/J-FASE-2022466
https://academic.hep.com.cn/fase/EN/Y2022/V9/I4/523

Concept	Equation	Description
Adjacent matrix	$A = [a i j]$	A matrix describing a finite graph, in which its element a_ij indicates the relationship from the ith node to the jth node
Network size	S	Number of nodes in the network
Connectance*	$C = L / S 2$	The proportion of realized links over all possible links. L means the total number of links in the network
Nestedness	–	The tendency for nodes to interact with subsets of the interaction partners of better-connected nodes^[¹⁵^]
Robustness	R₅₀	The number of primary removel needed to attain 50% of node loss^[¹⁶^]
Modularity*	$Q = 1 4 m ∑ i j (a i j − D i D j 2 m) s i s j$	The fraction of the edges that fall within the given groups minus the expected fraction if edges were distributed at random. Here m is the total number of edges. s_i = 1 if the ith node belongs to group 1 and s_i = −1 if it belongs to group 2^[¹⁷^]
Centrality	–	A measure describing the importance of nodes, including degree centrality, betweenness centrality and closeness centrality
Degree	$D i = ∑ j a i j + ∑ j a j i$	Number of links connected to the ith node
Closeness	$C i = 1 / ∑ j d j i$	A measure describing how close on average of the ith node to the other nodes. Here d_ji is the shortest path length from the jth node to the ith node
Betweenness	$B i = ∑ v ≠ i ≠ j σ v j (i) σ v j$	A measure describing the probability the ith node located in the shortest path from one node to another node. σ_vj is the number of shortest paths from the vth node to the jth node, and σ_vj(i) is the number of shortest paths from the vth node to the jth node which go through the ith node
Motif	–	Simple patterns of interconnections from which networks are built^[¹⁸^]
Rich core	–	A subgroup of nodes which have high degree and are well-connected with each other^[¹⁹^]
Compartment	–	Also known as cluster, module or community in graph theory. Usually a network can be divided into several compartments, which are subgroups of nodes. Within compartments, nodes are well connected, and between compartments, nodes are rarely connected^[²⁰^]

Tab.1 Summary table of the concepts in complex network theory

Fig.1 Substructures of networks: (a) a special motif: intraguild predation; (b) the core-periphery structure; and (c) a network consists of two compartments.

Fig.2 Three types of networks: (a) a food web in which the green nodes indicating producers and detritus, the blue nodes indicating consumers, and the red node indicating the top predator; (b) a pollination network with the bottom level as plants and the top level as pollinators; and (c) a co-occurrence network with nodes as OTUs (different colors indicates different taxa) and links as correlations (red for positive ones and green for negative ones).

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