Taylor's power law captures the effects of environmental variability on community structure: An example from fishes in the North Sea

Cobain, Matthew R D; Brede, Markus; Trueman, Clive N.

doi:10.1111/1365-2656.12923

Cited by 18 publications

(31 citation statements)

References 53 publications

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“…Indeed, a low corroboration of TPL was linked to a weak variance explanation of the regressions in Figure 1 (Supporting Information Figure S2). In the other traits, the range of trait expressions was similar to the variable range in other studies on TPL where strong TPL patterns were confirmed (Cobain et al, 2019;Kilpatrick & Ives, 2003). Therefore, we argue that in the mentioned traits the TPL slope is indeed close to one, indicating in these traits a Poisson random distribution of species traits in regional plant assemblages.…”

Section: Discussionsupporting

confidence: 83%

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Latitudinal gradients and scaling regions in trait space: Taylor’s power law in Japanese woody plants

Ulrich

Kusumoto

Shiono

et al. 2021

Global Ecol Biogeogr

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Aim Taylor's power law (TPL) is a variation of the variance:mean ratio and is often used to describe over‐ or underdispersed ecological distributions. We hypothesize that TPL is also applicable to the distribution of species traits and that the respective power law parameters might determine ecological functioning. Here, we aim to study this hypothesis in detail. Location East Asian islands, including the Japanese and Ryukyu archipelagos. Time period 1968–2015. Major taxa studied Gymnosperm and angiosperm woody plant species. Methods We used the geographical distribution of 946 Japanese woody plant species at the 10 km × 10 km grid cell level. Based on leaf and wood samples and literature data, we studied 10 important plant traits (maximum plant height, average fruit and seed size, specific leaf area, leaf thickness, wood density, leaf tannin and phenol content, and C/P and C/N ratios) and related trait variability to minimum absolute temperature, land and forest area and to the variability in forest cover and elevation using bi‐ and multivariate and piecewise regression analysis. Results The variability in the trait expression was well described by TPL. Average trait expression and the respective variability changed predictably along the latitudinal gradient, resulting in a general tendency towards trait clustering (TPL slopes > 1.0). Piecewise regression detected significant breakpoints in the TPL pattern for most traits. Minimum ambient temperature and latitude were the most important predictors of the variability in the observed TPL slopes. Main conclusions Taylor's power law appears to be trait specific and cannot be used as a diagnostic ecological character. We propose a new linear model to quantify ecological variability that includes average variable expressions and ecological covariates. We argue that common measures to quantify ecological variability based on the variance:mean ratio might give false impressions about the true degree of variability because they do not account for the variance–mean allometry.

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Section: Discussionsupporting

confidence: 83%

“…Previous authors have argued that TPL slopes vary systematically with environmental drivers that affect species abundances and spatial distributions (Cobain et al., 2019). In answer to our third question, our results corroborate this hypothesis in part.…”

Section: Discussionmentioning

confidence: 99%

Latitudinal gradients and scaling regions in trait space: Taylor’s power law in Japanese woody plants

Ulrich

Kusumoto

Shiono

et al. 2021

Global Ecol Biogeogr

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“…|− ϵ + 1| is the scaling exponent of the distribution. B : Taylor’s law as scaling law between standard deviation and mean species abundance for five TRs; ν /2 is the scaling exponent of Taylor’s law that is typically construed by using the variance [ 72 ], 〈 x 2 〉 ∼ 〈 x 〉 ν ; smaller ν means that fluctuations in abundance are more even and species are more regularly distributed; vice versa, species are more power-law distributed (as supported by Zip’s law) driven by stronger environmental effects [ 85 ] (in this case ST) determining portfolio effects with potential stabilizing effects [ 86 ] (this however neglects interaction topology). All exponents for five TRs are interpolated by black dashed lines in insets to emphasize abundance patterns transitions across TRs/seasons; transitions show a gradual second-order phase transition with higher Pareto-distributed fluctuations for higher temperature.…”

Section: Resultsmentioning

confidence: 99%

Temperature increase drives critical slowing down of fish ecosystems

Convertino

2021

PLoS ONE

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Fish ecosystems perform ecological functions that are critically important for the sustainability of marine ecosystems, such as global food security and carbon stock. During the 21st century, significant global warming caused by climate change has created pressing challenges for fish ecosystems that threaten species existence and global ecosystem health. Here, we study a coastal fish community in Maizuru Bay, Japan, and investigate the relationships between fluctuations of ST, abundance-based species interactions and salient fish biodiversity. Observations show that a local 20% increase in temperature from 2002 to 2014 underpins a long-term reduction in fish diversity (∼25%) played out by some native and invasive species (e.g. Chinese wrasse) becoming exceedingly abundant; this causes a large decay in commercially valuable species (e.g. Japanese anchovy) coupled to an increase in ecological productivity. The fish community is analyzed considering five temperature ranges to understand its atemporal seasonal sensitivity to ST changes, and long-term trends. An optimal information flow model is used to reconstruct species interaction networks that emerge as topologically different for distinct temperature ranges and species dynamics. Networks for low temperatures are more scale-free compared to ones for intermediate (15-20°C) temperatures in which the fish ecosystem experiences a first-order phase transition in interactions from locally stable to metastable and globally unstable for high temperatures states as suggested by abundance-spectrum transitions. The dynamic dominant eigenvalue of species interactions shows increasing instability for competitive species (spiking in summer due to intermediate-season critical transitions) leading to enhanced community variability and critical slowing down despite higher time-point resilience. Native competitive species whose abundance is distributed more exponentially have the highest total directed interactions and are keystone species (e.g. Wrasse and Horse mackerel) for the most salient links with cooperative decaying species. Competitive species, with higher eco-climatic memory and synchronization, are the most affected by temperature and play an important role in maintaining fish ecosystem stability via multitrophic cascades (via cooperative-competitive species imbalance), and as bioindicators of change. More climate-fitted species follow temperature increase causing larger divergence divergence between competitive and cooperative species. Decreasing dominant eigenvalues and lower relative network optimality for warmer oceans indicate fishery more attracted toward persistent oscillatory states, yet unpredictable, with lower cooperation, diversity and fish stock despite the increase in community abundance due to non-commercial and venomous species. We emphasize how changes in species interaction organization, primarily affected by temperature fluctuations, are the backbone of biodiversity dynamics and yet for functional diversity in contrast to taxonomic richness. Abundance and richness manifest gradual shifts while interactions show sudden shift. The work provides data-driven tools for analyzing and monitoring fish ecosystems under the pressure of global warming or other stressors. Abundance and interaction patterns derived by network-based analyses proved useful to assess ecosystem susceptibility and effective change, and formulate predictive dynamic information for science-based fishery policy aimed to maintain marine ecosystems stable and sustainable.

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“…|− ϵ + 1| is the scaling exponent of the distribution. B : Taylor’s law as scaling law between standard deviation and mean species abundance for five TRs; ν/ 2 is the scaling exponent of Taylor’s law that is typically construed by using the variance [54], ⟨ x 2 ⟩∼ ⟨ x ⟩ ν ; smaller ν means that fluctuations in abundance are more even and species are more regularly distributed; vice versa, species are more power-law distributed (as supported by Zip’s law) driven by stronger environmental effects [21] (in this case ST) determining portfolio effects with potential stabilizing effects [4] (this however neglects interaction topology). All exponents for five TRs are interpolated by black dashed lines in insets to emphasize abundance patterns transitions across TRs/seasons; transitions show a gradual second-order phase transition with higher Pareto-distributed fluctuations for higher temperature.…”

Section: Resultsmentioning

confidence: 99%

Temperature Increase Drives Critical Slowing Down of Fish Ecosystems

Convertino

2021

Preprint

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Fish ecosystems perform ecological functions that are critically important for the sustainability of marine ecosystems, as well as for global food security. During the 21st century, significant global warming caused by climate change has created novel challenges for fish ecosystems that threaten the global environmental and human health. Here, we study a coastal fish community in Maizuru Bay, Japan, and investigate the relationships between fluctuations of sea temperature and fish biodiversity and abundance. The global increase of temperature from 2002 to 2014 reduces fish diversity, while some species become more abundant and that causes ecological productivity to grow exponentially. The fish community is analyzed considering five temperature ranges: ≤10° C, 10-15° C, 15-20° C, 20-25° C, ≥25° C. In order to infer bidirectional interactions between species, an optimal information flow model is introduced in this study. We detect interdependencies between species and reconstruct species interaction networks that are functionally different for each temperature range. Networks for lower and higher temperature ranges are more scale-free compared to networks for the intermediate 15-20° C range in which the fish ecosystem experiences a first order phase transition from a locally stable state to a metastable state. Species-specific analysis is conducted by calculating the link salience and total outgoing information flow. Native species whose abundance is distributed more uniformly have a higher total outgoing information flow, and are the reference species (nodes in networks) of the most salient links. These species play an important role in maintaining the fish ecosystem stability. Species diversity, total interactions and entropy of species abundance in the fish community grow with the increase of temperature. This work provides a data-driven tool for analyzing and monitoring fish ecosystems under the pressure of global warming or other stressors. Macroecological and network-based analyses are useful to formulate science-based and accurate fishery policy to maintain marine fish ecosystems stable and sustainable.

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Taylor's power law captures the effects of environmental variability on community structure: An example from fishes in the North Sea

Cited by 18 publications

References 53 publications

Latitudinal gradients and scaling regions in trait space: Taylor’s power law in Japanese woody plants

Latitudinal gradients and scaling regions in trait space: Taylor’s power law in Japanese woody plants

Temperature increase drives critical slowing down of fish ecosystems

Temperature Increase Drives Critical Slowing Down of Fish Ecosystems

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