Effect sizes and standardization in neighbourhood models of forest stands: potential biases and misinterpretations

Stoll, Peter; Murrell, David J.; Newbery, David McClintock

doi:10.1111/2041-210x.12409

Cited by 6 publications

(3 citation statements)

References 13 publications

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“…The magnitude of effects on growth were quantified by calculating effect sizes as squared multiple partial correlation coefficients, or t 2 / ( t 2 + df resid ) (Cohen 1988, Rosenthal 1994, Nakagawa and Cuthill 2007). All models were fitted using alternatively no, linear and squared distance decay (Stoll et al 2015).…”

Section: Methodsmentioning

confidence: 99%

Including tree spatial extension in the evaluation of neighbourhood competition effects in Bornean rain forest

Newbery

Stoll

2020

Preprint

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Classical tree neighbourhood models use size variables acting at point distances. In a new approach here, trees were spatially extended as a function of their crown sizes, represented impressionistically as points within crown areas. Extension was accompanied by plasticity in the form of crown removal or relocation under the overlap of taller trees. Root systems were supposedly extended in a similar manner. For the 38 most abundant species in the focal size class (10 - <100 cm stem girth) in two 4-ha plots at Danum (Sabah), for periods P1 (1986-1996) and P2 (1996-2007), stem growth rate and tree survival were individually regressed against stem size, and neighbourhood conspecific (CON) and heterospecific (HET) basal areas within incremented radii. Model parameters were critically assessed, and statistical robustness in the modelling set by randomization testing. Classical and extended models differed importantly in their outcomes. Crown extension weakened the relationship of CON effect on growth versus plot species’ abundance, showing that models without plasticity over-estimated negative density dependence. A significant negative trend of difference in CON effects on growth (P2 − P1) versus CON or HET effect on survival in P1 was strongest with crown extension. Model outcomes did not then support an explanation of CON and HET effects being due to (asymmetric) competition for light alone. An alternative hypothesis is that changes in CON effects on small trees, largely incurred by a drought phase (relaxing light limitation) in P2, and following the more shaded (suppressing) conditions in P1, were likely due to species-specific (symmetric) root competition and mycorrhizal processes. The very high variation in neighbourhood composition and abundances led to a strong ‘neighbourhood stochasticity’, and hence to largely idiosyncratic species’ responses. A need to much better understand the roles of rooting structure and processes at the individual tree level was highlighted.

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Section: Methodsmentioning

confidence: 99%

Including tree spatial extension in the evaluation of neighbourhood competition effects in Bornean rain forest

Newbery

Stoll

2020

Preprint

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“…All models were fitted using alternatively no, linear, and squared distance decay (Stoll et al, 2015).…”

Section: Model Fittingmentioning

confidence: 99%

Including tree spatial extension in the evaluation of neighborhood competition effects in Bornean rain forest

Newbery

Stoll

2021

Ecology and Evolution

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“…The first option is to fit growth and/or survival models that take into account the identity and size of nearby neighbours (e.g. Comita, Muller-Landau, Aguilar, & Hubbell, 2010;Stoll, Murrell, & Newbery, 2015;Stoll & Newbery, 2005;Uriarte, Condit, Canham, & Hubbell, 2004). However, this requires repeated sampling over time in order to track the fate of every individual and very often such data are not available.…”

Section: Introductionmentioning

confidence: 99%

When do we have the power to detect biological interactions in spatial point patterns?

2018

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Uncovering the roles of biotic interactions in assembling and maintaining species‐rich communities remains a major challenge in ecology. In plant communities, interactions between individuals of different species are expected to generate positive or negative spatial interspecific associations over short distances. Recent studies using individual‐based point pattern datasets have concluded that (a) detectable interspecific interactions are generally rare, but (b) are most common in communities with fewer species; and (c) the most abundant species tend to have the highest frequency of interactions. However, it is unclear how the detection of spatial interactions may change with the abundances of each species, or the scale and intensity of interactions. We ask if statistical power is sufficient to explain all three key results. We use a simple two‐species model, assuming no habitat associations, and where the abundances, scale and intensity of interactions are controlled to simulate point pattern data. In combination with an approximation to the variance of the spatial summary statistics that we sample, we investigate the power of current spatial point pattern methods to correctly reject the null model of pairwise species independence. We show the power to detect interactions is positively related to both the abundances of the species tested, and the intensity and scale of interactions, but negatively related to imbalance in abundances. Differences in detection power in combination with the abundance distributions found in natural communities are sufficient to explain all the three key empirical results, even if all pairwise interactions are identical. Critically, many hundreds of individuals of both species may be required to detect even intense interactions, implying current abundance thresholds for including species in the analyses are too low. Sy n thesis. The widespread failure to reject the null model of spatial interspecific independence could be due to low power of the tests rather than any key biological process. Since we do not model habitat associations, our results represent a first step in quantifying sample sizes required to make strong statements about the role of biotic interactions in diverse plant communities. However, power should be factored into analyses and considered when designing empirical studies.

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Effect sizes and standardization in neighbourhood models of forest stands: potential biases and misinterpretations

Cited by 6 publications

References 13 publications

Including tree spatial extension in the evaluation of neighbourhood competition effects in Bornean rain forest

Including tree spatial extension in the evaluation of neighbourhood competition effects in Bornean rain forest

Including tree spatial extension in the evaluation of neighborhood competition effects in Bornean rain forest

When do we have the power to detect biological interactions in spatial point patterns?

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