Ecological network metrics: opportunities for synthesis

Lau, Matthew K.; Borrett, Stuart R.; Baiser, Benjamin; Gotelli, Nicholas J.; Ellison, Aaron M.

doi:10.1002/ecs2.1900

Cited by 86 publications

(64 citation statements)

References 162 publications

(210 reference statements)

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“…Some indicators may be calculated directly from the matrix (crop-livestock integration activity, productivity, dependency, efficiency). The other indicators are calculated by using the R software, with the package enaR (Lau et al 2017). After performing univariate and bivariate analyses, a principal component analysis was carried out with six indicators by using the R software (Lê et al 2008).…”

Section: Discussionmentioning

confidence: 99%

Crop-livestock integration determines the agroecological performance of mixed farming systems in Latino-Caribbean farms

Stark

García

Navegantes

et al. 2017

Agron. Sustain. Dev.

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Characterizing and understanding the complexity of numerous interactions occurring in mixed farming systems is still a methodological challenge. We hypothesize that farm functioning features in terms of crop-livestock integration practices impact the agroecological performance of the system, which will be also affected by the farm context. In order to analyze crop-livestock integration in a holistic way, a set of seventeen mixed farming systems from three contrasting socioeconomic regions of the humid tropics (Guadeloupe, Brazilian Amazonia, and Cuba) was selected in order to cover a wide range of crop-livestock integration situations. The ecological network analysis was applied to each farm in order to study the nutrient flow networks, expressed in nitrogen. The activity and flow organization of crop-livestock integration practices were characterized and the agroecological performance has been evaluated in terms of efficiency, resilience, productivity, and dependency of N flow networks. Here, we show for the first time that the range of crop-livestock integration is well characterized by the activity and organization of flows. Gradients of crop-livestock integration were well detected and described. Some agroecological performances were related to a particular socioeconomic context. Resource endowment influenced efficiency, according to the intensification level. The crop-livestock integration however contributed partially to the productivity of the system, being especially effective in promoting resilience. This study applies a suitable framework to analyze complex farming systems while linking their functioning and performance in an agroecological approach. Thus, comparison of contrasting systems was feasible here with the support of numerical and tangible figures for interpreting complex indicators (e.g., resilience), representing a useful tool for monitoring sustainability of agricultural systems in a dynamic and holistic way.

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Section: Discussionmentioning

confidence: 99%

Crop-livestock integration determines the agroecological performance of mixed farming systems in Latino-Caribbean farms

Stark

García

Navegantes

et al. 2017

Agron. Sustain. Dev.

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“…, Lau et al. ). We constructed SDNs for the HVMC using Spearman's rank correlation coefficient ( ρ ) computed between pairs of species‐specific species dominance indices D s (Eq.…”

Section: Dominance Network Analysismentioning

confidence: 99%

“…Network analysis is one of the most powerful approaches for dealing with complex, high‐dimensional data because the basic network structure still holds and can be computed when the dimensions of the data far exceed the number of data points (Lau et al. ).…”

Section: Dominance Network Analysismentioning

confidence: 99%

“…Microbial metagenomic data sets, for example, usually have hundreds, if not thousands, of operational taxonomic units (OTUs) sampled repeatedly through time or space. Network analysis is one of the most powerful approaches for dealing with complex, high-dimensional data because the basic network structure still holds and can be computed when the dimensions of the data far exceed the number of data points (Lau et al 2017).…”

Section: Roadmapmentioning

confidence: 99%

“…A variety of different methods grouped under the rubric of network analysis that emphasize species interactions and food webs can be used to analyze ecological systems (e.g., Junker and Schreiber 2008, Ings et al 2009, Lau et al 2017. We constructed SDNs for the HVMC using Spearman's rank correlation coefficient (q) computed between pairs of species-specific species dominance indices D s (Eq.…”

Section: Species Dominance Network (Sdns)mentioning

confidence: 99%

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Dominance network analysis provides a new framework for studying the diversity–stability relationship

Ellison

2019

Ecological Monographs

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The diversity–stability relationship is a long‐standing, central focus of community ecology. Two major challenges have impeded studies of the diversity–stability relationship (DSR): the difficulty in obtaining high‐quality longitudinal data sets; and the lack of a general theoretical framework that can encompass the enormous complexity inherent in “diversity,” “stability,” and their many interactions. Metagenomic “Big Data” now provide high quality longitudinal data sets, and the human microbiome project (HMP) offers an unprecedented opportunity to reinvigorate investigations of DSRs. We introduce a new framework for exploring DSRs that has three parts: (1) a cross‐scale measure of dominance with a simple mathematical form that can be applied simultaneously to individual species and entire communities and can be used to construct species dominance networks (SDNs); (2) analysis of SDNs based on special trio motifs, core‐periphery, rich‐club, and nested structures, and high salience skeletons; and (3) a synthesis of coarse‐scale core/periphery/community‐level stability modeling with fine‐scale analysis of SDNs that further reveals the stability properties of the community structures. We apply this new approach to data from the human vaginal microbiome of the HMP, simultaneously illustrating its utility in developing and testing theories of diversity and stability while providing new insights into the underlying ecology and etiology of a human microbiome‐associated disease.

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Beyond Kuhnian paradigms: Normal science and theory dependence in ecology

Layman

Rypel

2023

Ecology and Evolution

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The Structure of Scientific Revolutions by Thomas Kuhn has influenced scientists for decades. It focuses on a progression of science involving periodic, fundamental shifts—revolutions—from one existing paradigm to another. Embedded in this theory is the concept of normal science, that is, scientists work within the confines of established theory, a process often compared to a type of puzzle‐solving. This Kuhnian aspect of scientific research has received little attention relative to the much‐scrutinized concepts of revolutions and paradigms. We use Kuhn's normal science framework to reflect on the way ecologists practice science. This involves a discussion of how theory dependence influences each step of the scientific method, specifically, how past experiences and existing research frameworks guide the way ecologists acquire knowledge. We illustrate these concepts with ecological examples, including food web structure and the biodiversity crisis, emphasizing that the way one views the world influences how that person engages in scientific research. We conclude with a discussion of how Kuhnian ideas inform ecological research at practical levels, such as influences on grant funding allocation, and we make a renewed call for the inclusion of philosophical foundations of ecological principles in pedagogy. By studying the processes and traditions of how science is carried out, ecologists can better direct scientific insight to address the world's most pressing environmental problems.

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Ecological network metrics: opportunities for synthesis

Cited by 86 publications

References 162 publications

Crop-livestock integration determines the agroecological performance of mixed farming systems in Latino-Caribbean farms

Crop-livestock integration determines the agroecological performance of mixed farming systems in Latino-Caribbean farms

Dominance network analysis provides a new framework for studying the diversity–stability relationship

Beyond Kuhnian paradigms: Normal science and theory dependence in ecology

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