Vegetation, herbivores and fires in savanna ecosystems: A network perspective

Antonio Bodini, Nicola Clerici

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

© 2016 Elsevier B.V.The dynamics of savanna ecosystems depends on the interplay between multiple factors such as grazing, browsing, fires, rainfall regime and interactions between grass and woody vegetation. In most modelling applications this interplay may not be fully understood because some of these drivers enter the models as dynamically independent factors. In this paper we consider such factors as dynamic variables. To analyze their interplay we focus on the structure of the interactive network of variables and exploit the properties of signed digraphs using the algorithm of Loop Analysis. Qualitative signed digraphs for the savanna ecosystem are developed and their predictions used to interpret patterns of abundance observed in case studies selected from the literature. The outcomes of this exercise unveil that: 1) the structure of the interactions is appropriate locus for the explanation of patterns observed in savannas; 2) signed digraph can help disentangling causative mechanisms by linking correlation patterns, source of change and network structure. This study highlights that central to the understanding of savanna dynamics is our ability to diagram the important relationships and understand how they interrelate with sources of variations to cause ecosystem change.
Original languageEnglish (US)
Pages (from-to)36-46
Number of pages11
JournalEcological Complexity
DOIs
StatePublished - Dec 1 2016

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savanna
savannas
herbivore
herbivores
vegetation
ecosystems
ecosystem
browsing
exercise
grazing
diagram
grass
case studies
grasses
rain
rainfall
loci
prediction
modeling

Cite this

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title = "Vegetation, herbivores and fires in savanna ecosystems: A network perspective",
abstract = "{\circledC} 2016 Elsevier B.V.The dynamics of savanna ecosystems depends on the interplay between multiple factors such as grazing, browsing, fires, rainfall regime and interactions between grass and woody vegetation. In most modelling applications this interplay may not be fully understood because some of these drivers enter the models as dynamically independent factors. In this paper we consider such factors as dynamic variables. To analyze their interplay we focus on the structure of the interactive network of variables and exploit the properties of signed digraphs using the algorithm of Loop Analysis. Qualitative signed digraphs for the savanna ecosystem are developed and their predictions used to interpret patterns of abundance observed in case studies selected from the literature. The outcomes of this exercise unveil that: 1) the structure of the interactions is appropriate locus for the explanation of patterns observed in savannas; 2) signed digraph can help disentangling causative mechanisms by linking correlation patterns, source of change and network structure. This study highlights that central to the understanding of savanna dynamics is our ability to diagram the important relationships and understand how they interrelate with sources of variations to cause ecosystem change.",
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Vegetation, herbivores and fires in savanna ecosystems: A network perspective. / Bodini, Antonio; Clerici, Nicola.

In: Ecological Complexity, 01.12.2016, p. 36-46.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Vegetation, herbivores and fires in savanna ecosystems: A network perspective

AU - Bodini, Antonio

AU - Clerici, Nicola

PY - 2016/12/1

Y1 - 2016/12/1

N2 - © 2016 Elsevier B.V.The dynamics of savanna ecosystems depends on the interplay between multiple factors such as grazing, browsing, fires, rainfall regime and interactions between grass and woody vegetation. In most modelling applications this interplay may not be fully understood because some of these drivers enter the models as dynamically independent factors. In this paper we consider such factors as dynamic variables. To analyze their interplay we focus on the structure of the interactive network of variables and exploit the properties of signed digraphs using the algorithm of Loop Analysis. Qualitative signed digraphs for the savanna ecosystem are developed and their predictions used to interpret patterns of abundance observed in case studies selected from the literature. The outcomes of this exercise unveil that: 1) the structure of the interactions is appropriate locus for the explanation of patterns observed in savannas; 2) signed digraph can help disentangling causative mechanisms by linking correlation patterns, source of change and network structure. This study highlights that central to the understanding of savanna dynamics is our ability to diagram the important relationships and understand how they interrelate with sources of variations to cause ecosystem change.

AB - © 2016 Elsevier B.V.The dynamics of savanna ecosystems depends on the interplay between multiple factors such as grazing, browsing, fires, rainfall regime and interactions between grass and woody vegetation. In most modelling applications this interplay may not be fully understood because some of these drivers enter the models as dynamically independent factors. In this paper we consider such factors as dynamic variables. To analyze their interplay we focus on the structure of the interactive network of variables and exploit the properties of signed digraphs using the algorithm of Loop Analysis. Qualitative signed digraphs for the savanna ecosystem are developed and their predictions used to interpret patterns of abundance observed in case studies selected from the literature. The outcomes of this exercise unveil that: 1) the structure of the interactions is appropriate locus for the explanation of patterns observed in savannas; 2) signed digraph can help disentangling causative mechanisms by linking correlation patterns, source of change and network structure. This study highlights that central to the understanding of savanna dynamics is our ability to diagram the important relationships and understand how they interrelate with sources of variations to cause ecosystem change.

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