Structural Equation Modeling and Natural Systems

By J. Grace. 2006

1,867 citations recorded by the source corpus.

Subfields: Ecological Modeling, Nature and Landscape Conservation, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/4579b0b9acf0424ef5a0cdcc3e92624fd75d404e

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Citations in the corpus

Humidity levels drive reproductive modes and phylogenetic diversity of amphibians in the Brazilian Atlantic Forest (2012, methodology): “For further details on path analysis, including applications in ecology, see Shipley (2000) and Grace (2006).”
Accounting for the causal basis of collinearity when measuring the effects of habitat loss versus habitat fragmentation (2016, methodology): “…was re-scaled to have the same mean and variance as the landscape metrics 219 (which was necessary to calculate the size of indirect effects; Grace 2006); (2) landscape metrics 220 had homogeneity of variance, whereas those measured by Smith et al. (2009) were 221 heteroscedastic; and (3)…”
Light, earthworms, and soil resources as predictors of diversity of 10 soil invertebrate groups across monocultures of 14 tree species (2016, neutral): “…communities, plant species often have divergent impacts on the diversity of soil animal communities; this “ plant species identity ” effect is often larger than effects of plant species richness (Wardle et al., 2003, 2006; De Deyn et al., 2004; Ball et al., 2009; Eissfeller et al., 2013b).”
Scaling from leaf traits to fire behaviour: community composition predicts fire severity in a temperate forest (2011, methodology): “…‘A’ versions of eachmodel, we tested for a spatial autocorrelation not captured by our environmental variables by including nearest-neighbour fire severity as an additional causal variable on fire severity as suggested in Grace (2006) as a method for dealing with potential spatial autocorrelation.”
Nitrification is linked to dominant leaf traits rather than functional diversity (2011, methodology): “ing and the model-fitting processes (Grace 2006).”
The priority of prediction in ecological understanding (2017, background): “The literature on causal modelling is deep (Grace 2006, Pearl 2009a, b) and well beyond the scope of this article; however, linking mechanistic understanding to accurate predictions is an important future challenge facing ecologists (McGill and Nekola 2010).”
The spatial scale of plant-animal interactions: effects of resource availability and habitat structure (2011, methodology): “…habitat features on frugivory and seed predation We evaluated how the spatial structure of plant– animal interactions at different scales was conditioned by, simultaneously, fruit/seed resource availability and habitat structure by means of structural equation models (SEM; Grace 2006).”
A method for exploring the structure of behavioural syndromes to allow formal comparison within and between data sets (2010, methodology): “Determining fit and thus the ability to compare different models of syndrome structure is contingent on multivariate normality (Kline 2005; Grace 2006).”
Spatially explicit structural equation modeling (2014, methodology): “The standard advice on the evaluation of model fit, such as nonsignificant v2 tests and acceptable values for other indices of model fit (Grace 2006, Kline 2011), applies to the evaluation of model fit across lag distance with some caveats.”
Phenotypic selection on floral scent: trade-off between attraction and deterrence? (2011, methodology): “In addition, this method allows the consideration of multidimensional characters, like scent bouquets, by means of latent variables (Grace 2006).”
Plant diversity enhances productivity and soil carbon storage (2018, methodology): “Specifically, our study was designed to address the following two questions: First, how do climate, soil properties, and human disturbance affect SOC storage via direct effects and indirect effects mediated by community properties, such as species richness (SR), aboveground net primary productivity ”
Functional diversity supports the physiological tolerance hypothesis for plant species richness along climatic gradients (2014, methodology): “One approach for integrating multiple metrics of functional diversity in hypothesis tests is through the use of latent variables in structural equation modelling (SEM; Grace 2006).”
Vertebrate herbivore-induced changes in plants and soils: linkages to ecosystem functioning in a semi-arid steppe (2013, methodology): “A large P value (>0 05) associated with the chi-square value indicates that the covariance structure of the data does not differ significantly from the expected, based on the model (Grace 2006).”
Global patterns of ecologically unequal exchange: Implications for sustainability in the 21st century (2021, methodology): “SEMs are networks of variables connected through paths that represent statistical relationships (Grace, 2006; Lefcheck, 2016).”
Plant species richness and functional groups have different effects on soil water content in a decade‐long grassland experiment (2018, methodology): “The adequacy of the model was tested with chi-squared tests (χ2 tests), AIC, and root mean square error of approximation (RMSEA; Grace, 2006).”
How fundamental plant functional trait relationships scale‐up to trade‐offs and synergies in ecosystem services (2012, methodology): “…prior knowledge of the functioning to the study ecosystem and relevant variables (Lavorel et al. 2011), an initial hypothesized or construct model (Grace 2006) was specified as a hierarchical model with environmental parameters influencing community trait parameters, and these then regulating…”