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Steven I. Higgins

Researcher at University of Bayreuth

Publications -  126
Citations -  15473

Steven I. Higgins is an academic researcher from University of Bayreuth. The author has contributed to research in topics: Vegetation & Biome. The author has an hindex of 55, co-authored 121 publications receiving 13944 citations. Previous affiliations of Steven I. Higgins include University of the Witwatersrand & Helmholtz Centre for Environmental Research - UFZ.

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Pine invasions in the southern hemisphere: modelling interactions between organism, environment and disturbance

TL;DR: This study shows that by incorporating interactions and mechanisms into their models the authors can potentially reduce the number of factors needed to predict plant invasions, and improves the understanding of invasions.
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Influence of competition and rainfall manipulation on the growth responses of savanna trees and grasses

TL;DR: The results suggest that, in savannas, increasing rainfall serves to increase the competitive pressure exerted by grasses on trees, and recruitment into the adult tree stage from the juvenile stage is most likely in drought years when there is little competition from grass for resources and grass fuel loads are low.
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Biological and geophysical feedbacks with fire in the Earth system

TL;DR: In this paper, a conceptual framework of how plant traits determine the flammability of ecosystems and interact with climate and weather to influence fire regimes is presented, and the authors explore how these evolutionary and ecological processes scale to impact biogeochemical and Earth system processes.
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Connecting dynamic vegetation models to data – an inverse perspective

TL;DR: It is explained how Bayesian methods allow direct estimates of parameters and processes, encoded in prior distributions, to be combined with inverse estimates, encodedin likelihood functions, in order to bridge the gap in parameterization of dynamic vegetation models.
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The distribution of tree and grass roots in savannas in relation to soil nitrogen and water

TL;DR: In this article, the root distribution of trees and grasses relative to soil nitrogen and water profiles is described and the proportion of tree and grass fine roots at each soil depth are estimated using the δ 13 C values of fine roots and the ε 13 C end members of the fine roots of the dominant trees and Grasses at both mesic and arid sites.