Assessing the fire resilience of the savanna tree component through a functional approach

Altomare, Monize; Vasconcelos, Heraldo L.; Raymundo, Diego; Lopes, Sérgio de Faria; Vale, Vagner Santiago do

doi:10.1016/j.actao.2021.103728

Cited by 8 publications

(12 citation statements)

References 82 publications

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“…Most empirical studies measuring response trait diversity do so for trees ( e.g ., Craven et al . 2016; Altomare et al . 2021; Schnabel et al .…”

Section: Existing Response Diversity Studiesmentioning

confidence: 99%

“…(e) These divergent nonlinear responses produced a range of first derivatives that changed as a function of grazing pressure, in turn producing (g) grazing pressure-dependent response diversity which was on, average, high in terms of dissimilarity, and was zero-spanning at intermediate grazing pressure. (c) Finally, consider a case (based on Altomare et al . 2021), where the density of several tree species responded nonlinearly to fire frequency with different functional forms.…”

Section: Measuring Response Diversity Empiricallymentioning

confidence: 99%

“…2021), where the density of several tree species responded nonlinearly to fire frequency with different functional forms. This might occur if some species were highly sensitive to burning [brown line] while others were disturbance specialists that require nutrient inputs from fire or reduced competition from dominant fire-sensitive species (Altomare et al . 2021).…”

Section: Measuring Response Diversity Empiricallymentioning

confidence: 99%

“…Some studies measuring the dispersion of functional response traits explicitly do so after defining functional effect groups (Laliberté et al 2010;Thornhill et al 2018;Sasaki et al 2019;Morel et al 2020), producing a response diversity measure closely aligned to the Elmqvist et al (2003) definition, which specifies that response diversity should be measured among species contributing to the same ecosystem function (though subsequent definitions relax this requirement; e.g., Mori et al 2013). Most empirical studies measuring response trait diversity do so for trees (e.g., Craven et al 2016;Altomare et al 2021;Schnabel et al 2021) and other groups of plants (e.g., Mandle & Ticktin 2015;Döbert et al 2017;Morel et al 2020), or for freshwater or terrestrial invertebrates (e.g., Mumme et al 2015;Thornhill et al 2018).…”

Section: Introductionmentioning

confidence: 99%

“…(e) These divergent nonlinear responses produce a range of first derivatives that change as a function of grazing pressure, in turn producing (g) grazing pressuredependent response diversity which is on, average, high in terms of dissimilarity, and is zero-spanning at intermediate grazing pressure. (c) Finally, consider a case (based onAltomare et al 2021), where the density of several tree species responds nonlinearly to fire frequency with different functional forms. This might occur if some species are highly sensitive to burning [brown line] while others are disturbance specialists that require nutrient inputs from fire or reduced competition from dominant fire-sensitive species(Altomare et al 2021).…”

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confidence: 99%

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How to measure response diversity

Ross

Petchey

Sasaki

et al. 2022

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Taxonomic diversity metrics are, at best, proxies for the inter- and intraspecific trait differences that mechanistically underlie the insurance effect of biodiversity—that diversity enhances and stabilises aggregate ecosystem properties. In theory, variation in functional (e.g., biomass) responses to environmental change can buffer and maintain ecosystem functioning. This variation, termed response diversity, is therefore a potentially critical determinant of ecological stability. However, response diversity has yet to be widely quantified, possibly due to difficulties in its measurement. Even when it has been measured, approaches have varied. Here, we review methods for measuring response diversity and propose a methodological framework for quantifying response diversity from experimental or observational data, which can be practically applied in lab and field settings across a range of taxa. Our approach, which is based on environment-dependent functional responses to any biotic or abiotic environmental variable, is conceptually simple and robust to any form of environmental response, including nonlinear responses. By capturing even subtle inter- or intraspecific variation in environmental responses, and environment-dependencies in response diversity, we hope this framework will motivate tests of the diversity-stability relationship from a new perspective, and provide an approach for mapping, monitoring, and protecting this critical element of biodiversity.

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“…Most empirical studies measuring response trait diversity do so for trees ( e.g ., Craven et al . 2016; Altomare et al . 2021; Schnabel et al .…”

Section: Existing Response Diversity Studiesmentioning

confidence: 99%

Section: Measuring Response Diversity Empiricallymentioning

confidence: 99%

Section: Measuring Response Diversity Empiricallymentioning

confidence: 99%