Understanding the role of direct and indirect interactions in mediating local plant diversity

Martyn, Trace E.

doi:10.14264/uql.2020.824

Cited by 5 publications

(5 citation statements)

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“…The resulting dataset includes between 29 to over 1000 counts of individual plant seed production from 22 different focal species (with a median of 108 observations per species), in addition to the identity and densities of all neighbouring individuals within the interaction neighbourhood of each focal plant. Interaction neighbourhoods varied in radius from 3 to 5 cm depending on the size of the focal species (Martyn 2020). Total neighbourhood diversity was 71 wildflower species, 19 of which were recorded fewer than 10 times across the whole dataset.…”

Section: Supplementary Methodsmentioning

confidence: 99%

Estimating interaction matrices from performance data for diverse systems

Bimler

Mayfield

Martyn

et al. 2022

Preprint

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Network theory allows us to understand complex systems by evaluating how their constituent elements interact with one another. Such networks are built from matrices which describe the effect of each element on all others. Quantifying the strength of these interactions from empirical data can be difficult, however, because the number of potential interactions increases non-linearly as more elements are included in the system, and not all interactions may be empirically observable when some elements are rare. We present a novel modelling framework which estimates the strength of pairwise interactions in diverse horizontal systems, using measures of species performance in the presence of varying densities of their potential interaction partners. Our method allows us to directly estimate pairwise effects when they are statistically identifiable and approximate pairwise effects when they would otherwise be statistically unidentifiable. The resulting interaction matrices can include positive and negative effects, the effect of a species on itself, and are non-symmetrical. The advantages of these features are illustrated with a case study on an annual wildflower community of 22 focal and 52 neighbouring species, and a discussion of potential applications of this framework extending well beyond plant community ecology.

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Section: Supplementary Methodsmentioning

confidence: 99%

Estimating interaction matrices from performance data for diverse systems

Bimler

Mayfield

Martyn

et al. 2022

Preprint

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“…The first assumes that many species have similar effects on one another and can be grouped a priori according to biological factors (e.g. traits, life form; Martyn, 2020; Uriarte et al, 2004). The second assumes that a majority of interactions are weak and hence can be removed from the model through variable selection procedures (Mutshinda et al, 2009; Weiss‐Lehman et al, 2022), resulting in a sparse interaction network.…”

Section: Discussionmentioning

confidence: 99%

Estimating interaction strengths for diverse horizontal systems using performance data

et al. 2023

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Network theory allows us to understand complex systems by evaluating how their constituent elements interact with one another. Such networks are built from matrices which describe the effect of each element on all others. Quantifying the strength of these interactions from empirical data can be difficult, however, because the number of potential interactions increases nonlinearly as more elements are included in the system, and not all interactions may be empirically observable when some elements are rare. We present a novel modelling framework which uses measures of species performance in the presence of varying densities of their potential interaction partners to estimate the strength of pairwise interactions in diverse horizontal systems. Our method allows us to directly estimate pairwise effects when they are statistically identifiable and to approximate pairwise effects when they would otherwise be statistically unidentifiable. The resulting interaction matrices can include positive and negative effects, the effect of a species on itself, and allows for non‐symmetrical interactions. We show how to link the parameters inferred by our framework to a population dynamics model to make inferences about the effect of interactions on community dynamics and diversity. The advantages of these features are illustrated with a case study on an annual wildflower community of 22 focal and 52 neighbouring species, and a discussion of potential applications of this framework extending well beyond plant community ecology.

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“…To assess species' responses to the environment in the presence and absence of neighbours, we randomly assigned three subplots per species per plot to a neighbour removal treatment and left the remaining three subplots with naturally occurring assemblages. For the thinned subplots, we removed all neighbouring plants rooting within a 7.5 cm radius of the focal individual as per protocol described in Mayfield and Stouffer (2017), appropriate for capturing most direct plant–plant interactions in this system (Martyn, 2020). We recorded the abundance and identity of all neighbouring plants within the interaction neighbourhood during peak flowering in September.…”

Section: Methodsmentioning

confidence: 99%

Individual vital rates respond differently to local‐scale environmental variation and neighbour removal

Catling,

Mayfield,

Dwyer

2024

Journal of Ecology

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Understanding how plant fitness varies along natural gradients is critical for predicting responses to environmental change. However, individual vital rates are often used as fitness proxies without knowing how other vital rates vary along the same gradients. We investigated how canopy cover, plant–plant interactions, water availability and soil properties influenced the emergence, survival, seed production and population growth rates of eight annual plant species in semi‐arid Western Australia. We sowed seeds into sun‐exposed and shaded blocks across a reserve, removed all neighbouring plants from half of the interaction neighbourhoods, and used rainout shelters to reduce and increase precipitation relative to ambient plots. Canopy cover had strong negative effects on emergence, but few direct impacts on other vital rates and population growth rates. Direct competitive effects on survival and seed production were rare, although evident for population growth rate for 3/8 species. Competition was stronger in open than shaded plots for half of the species. Canopy cover also interacted with the watering treatment to influence survival of half of the species, but watering alone had few direct impacts on species' vital and population growth rates. We found only positive significant correlations between pairs of rates, and survival and seed production were far more frequently correlated with population growth rate than emergence. Synthesis. Our study illustrates that vital rates can respond to the same local‐scale environmental variation in different ways that are likely not driven by life history trade‐offs. We caution against using emergence as a proxy for population growth rate and emphasise that no single vital rate was a reliable fitness proxy overall. Interactions among abiotic and biotic factors were important drivers of vital and population growth rates for some species, highlighting the need to account for plant–plant interactions when predicting population responses to environmental change.

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Understanding the role of direct and indirect interactions in mediating local plant diversity

Cited by 5 publications

References 0 publications

Estimating interaction matrices from performance data for diverse systems

Estimating interaction matrices from performance data for diverse systems

Estimating interaction strengths for diverse horizontal systems using performance data

Individual vital rates respond differently to local‐scale environmental variation and neighbour removal

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