Shifting Macroecological Patterns and Static Theory Failure in a Stressed Alpine Plant Community

Franzman, Juliette; Brush, Micah; Umemura, Kaito; Ray, Courtenay A.; Blonder, Benjamin; Harte, John

doi:10.22541/au.159527004.40155464

Cited by 5 publications

(9 citation statements)

References 15 publications

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“…(2018) show that in the highly fragmented and manipulated UK, METE under‐predicts plant species richness derived from upscaling data from small plots. Franzman et al (2021) show that in an alpine plant community, both the SAR and the SAD increasingly deviate over time from METE predictions during several years of drought stress.…”

Section: Introductionmentioning

confidence: 99%

DynaMETE: a hybrid MaxEnt‐plus‐mechanism theory of dynamic macroecology

2021

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The Maximum Entropy Theory of Ecology (METE) predicts the shapes of macroecological metrics in relatively static ecosystems, across spatial scales, taxonomic categories and habitats, using constraints imposed by static state variables. In disturbed ecosystems, however, with time‐varying state variables, its predictions often fail. We extend macroecological theory from static to dynamic by combining the MaxEnt inference procedure with explicit mechanisms governing disturbance. In the static limit, the resulting theory, DynaMETE, reduces to METE but also predicts a new scaling relationship among static state variables. Under disturbances, expressed as shifts in demographic, ontogenic growth or migration rates, DynaMETE predicts the time trajectories of the state variables as well as the time‐varying shapes of macroecological metrics such as the species abundance distribution and the distribution of metabolic rates over individuals. An iterative procedure for solving the dynamic theory is presented. Characteristic signatures of the deviation from static predictions of macroecological patterns are shown to result from different kinds of disturbance. By combining MaxEnt inference with explicit dynamical mechanisms of disturbance, DynaMETE is a candidate theory of macroecology for ecosystems responding to anthropogenic or natural disturbances.

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Section: Introductionmentioning

confidence: 99%

DynaMETE: a hybrid MaxEnt‐plus‐mechanism theory of dynamic macroecology

2021

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“…Pursuing that idea, we might more generally expect the predictions of a top-down MaxEnt approach to fail under ecological disturbances that sufficiently alter the fitness landscape, resulting in dynamic, not static, state variables. This indeed appears to be the case for METE's prediction of the species-abundance distribution (SAD) and the species-area relationship (SAR), as discussed elsewhere 7,15,34,35,38 . An implication of this is that a survey of highly disturbed ecosystems with transitioning state variables, might reveal significant deviations from Eq.…”

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confidence: 64%

An Equation of State Unifies Diversity, Productivity, Abundance and Biomass

Harte

Brush

Newman

et al. 2022

Preprint

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To advance understanding of biodiversity and ecosystem function, ecologists seek widely applicable relationships among species diversity and other ecosystem characteristics such as species productivity, biomass, and abundance1-4. These metrics vary widely across ecosystems and no relationship among any combination of them that is valid across habitats, taxa, and spatial scales, has heretofore been found. Here we derive such a relationship, an equation of state, among species richness, energy flow, biomass and abundance by combining results from the Maximum Entropy Theory of Ecology5-7 and the Metabolic Theory of Ecology8,9. It accurately captures the relationship among these state variables in 42 data sets, including vegetation and arthropod communities, that span a wide variety of spatial scales and habitats. The success of our ecological equation of state opens opportunities for predicting difficult-to-measure state variables from measurements of others, adds support for two current theories in ecology, and is a step toward unification in ecology.

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“…The dynamics are then out of steady state, and the state variables alone are not sufficient to describe the macroecological patterns. For example, Franzman et al (2021) analyzed the change in state variables over time in a declining alpine meadow and found that macroecological patterns moved away from METE predictions over a six year period of observation. Here, we instead analyze how land use change affects deviation from METE predictions assuming that the deviation in time at any given land use type is relatively static.…”

Section: Implications For Future Mete Studies In Anthropogenic Landscapesmentioning

confidence: 99%

“…METE has been found to well describe empirical patterns across diverse taxa and habitats (Harte 2011;White et al 2012;Xiao et al 2015). However, there is increasing evidence that these predictions perform less well in disturbed ecosystems (Carey et al 2006;Rominger et al 2016;Newman et al 2020;Franzman et al 2021;Harte et al 2021). In the context of METE, most disturbance has been characterized by ecosystems with rapidly changing state variables, as METE seems to well describe ecosystems where state variables are relatively constant in time.…”

Section: Introductionmentioning

confidence: 99%

“…Anthropogenic disturbance impacts the form of macroecological patterns (Gray et al 1979; Hill and Hamer 1998; Dornelas et al 2009; Newman 2019), including through land use changes (Simons et al 2015; Xu et al 2019). An effective method for analyzing the impacts of disturbance on biodiversity is comparing empirical patterns to theoretically expected shapes (Kempton and Taylor 1974; Carey et al 2006; Supp et al 2012; Matthews and Whittaker 2015; Newman et al 2020; Franzman et al 2021) and relating deviations to the type of disturbance. To interpret macroecological patterns in this way, we require a theoretical prediction for what these different patterns should look like in ecosystems that have not been disturbed or managed.…”

Section: Introductionmentioning

confidence: 99%

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Land use change through the lens of macroecology: insights from Azorean arthropods and the Maximum Entropy Theory of Ecology

Brush¹,

Matthews

Borges

et al. 2021

Preprint

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Human activity and land management practices, in particular land use change, have resulted in the global loss of biodiversity. These types of disturbances affect the shape of macroecological patterns, and analyzing these patterns can provide insights into how ecosystems are affected by land use change. The Maximum Entropy Theory of Ecology (METE) simultaneously predicts many of these patterns using a set of ecological state variables: the number of species, the number of individuals, and the total metabolic rate. The theory's predictions have been shown to be successful across habitats and taxa in undisturbed natural ecosystems, although previous tests of METE in relation to disturbance have focused primarily on systems where the state variables are changing relatively quickly. Here, we assess predictions of METE applied to a different type of disturbance: land use change. We use METE to simultaneously predict the species abundance distribution (SAD), the metabolic rate distribution of individuals (MRDI), and the species--area relationship (SAR) and compare these predictions to arthropod data from 96 sites at Terceira Island in the Azores archipelago across four different land uses of increasing management intensity: 1. native forest, 2. exotic forest, 3. semi-natural pasture, and 4. intensive pasture. Across these patterns, we find that the forest habitats are the best fit by METE predictions, while the semi-natural pasture consistently provided the worst fit. The intensive pasture is intermediately well fit for the SAD and MRDI, and comparatively well fit for the SAR, though the residuals are not normally distributed. The direction of failure of the METE predictions at the pasture sites is likely due to the hyper-dominance of introduced spider species present there. We hypothesize that the particularly poor fit for the semi-natural pasture is due to the mix of arthropod communities out of equilibrium and the changing management practices throughout the year, leading to greater heterogeneity in composition and complex dynamics that violate METE's assumption of static state variables. The comparative better fit for the intensive pasture could then result from more homogeneous arthropod communities that are well adapted to intensive management, and thus whose state variables are less in flux.

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Shifting Macroecological Patterns and Static Theory Failure in a Stressed Alpine Plant Community

Cited by 5 publications

References 15 publications

DynaMETE: a hybrid MaxEnt‐plus‐mechanism theory of dynamic macroecology

DynaMETE: a hybrid MaxEnt‐plus‐mechanism theory of dynamic macroecology

An Equation of State Unifies Diversity, Productivity, Abundance and Biomass

Land use change through the lens of macroecology: insights from Azorean arthropods and the Maximum Entropy Theory of Ecology

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