Temporal variation of keystone species and their impact on system performance in a South African estuarine ecosystem

Arnab Banerjee, Ursula M. Scharler, Brian D. Fath and Santanu Ray

Ecological Modelling, 2017, vol. 363, issue C, 207-220

Abstract: Anthropogenic intervention along with natural variability can both influence and compromise continued ecosystem functioning. Ecological network analysis (ENA) was used to explore ecosystem functioning following disturbances to food web networks of a South African estuary, Mdloti, under different seasons. Keystone species, in particular, play an important structural role in spite of having low levels of presence in terms of biomass. From networks of carbon exchanges, the keystone species are identified which include high trophic level carnivorous fish species like Argyrosomus japonicus, Caranx sexfasciatus and Monodactylus falciformis. It is observed that keystone species differed between seasons, according to changing conditions of the estuary. The positive and negative direct and indirect effects that the keystone species have on the different components of the system are evaluated by a Mixed Trophic Impacts (MTI) analysis and results of the direct-indirect impacts analysis are not consistent across seasons.Results reinforce the fact that the keystone species are context dependent as they show variation over the different networks following species composition change following alteration of the estuaries physical status and season. To simulate disturbance, the keystone species biomass in the initial five networks was changed by 10% in stepwise intervals up to ± 99% and it was observed that the system is somewhat resistant to the perturbation effects of the keystone species.

Keywords: Food web; Ecological network analysis; Mixed trophic impacts; Keystoneness index; Mdloti estuary (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:363:y:2017:i:c:p:207-220

DOI: 10.1016/j.ecolmodel.2017.09.009

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