Reconnecting environs to their environment

Borrett, Stuart R.; Freeze, Michael

doi:10.1016/j.ecolmodel.2010.10.015

Cited by 14 publications

(14 citation statements)

References 71 publications

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“…We applied Allesina and Bondavalli's (2003) AVG2 balancing algorithm to 15 models that were not initially at steady state because this technique tends to generate the least distortion of network properties. This is the same set of models used in several recent network studies (Borrett and Salas, 2010;Borrett and Freeze, 2011;Salas and Borrett, 2011), and the model data are available from http://people.uncw.edu/borretts/research.html.…”

Section: Model Inputmentioning

confidence: 99%

“…Borrett and Freeze (2011) focused on the distinction between the idealized and realized forms of the I/D ratio. Here we focus on contrasting the input and output oriented analyses.…”

Section: Ecological Network Analysismentioning

confidence: 99%

“…Its analytical advantage is that the system flows are scaled with the observed, typically non-homogeneous boundary fluxes. Borrett and Freeze (2011) showed that the quantitative and qualitative results could be changed by this shift in perspective, highlighting the importance of the system's connection to its broader environment. For example, the wet season model of carbon flux in the Everglades graminoid marshes (Ulanowicz et al, 2000;Heymans et al, 2002) exhibits the dominance of indirect effects when analyzed with the realized method (I/D = 1.2) but does not when analyzed with the unit approach (I/D= 0.81).…”

Section: Introductionmentioning

confidence: 99%

“…Alternatively, the realized calculation uses the observed boundary flow vector instead of an input vector of ones. This approach was first introduced by Borrett et al (2006) but was clarified and formalized in Borrett and Freeze (2011). Its analytical advantage is that the system flows are scaled with the observed, typically non-homogeneous boundary fluxes.…”

Section: Introductionmentioning

confidence: 99%

“…For example, Borrett et al (2006) used I/D to show the temporal consistency of the organization of the Neuse River Estuary ecosystem, and Baird et al (2009) found that indirect effects were dominant in the Sylt-Rømo Bight ecosystem regardless of the model aggregation scheme. Borrett and Freeze (2011) distinguished between two ways of calculating this ratio that they termed the unit and realized formulations. The unit calculation is the traditional approach that is performed after a classic systems analysis technique is applied.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Equivalence of the realized input and output oriented indirect effects metrics in Ecological Network Analysis

Borrett¹,

Freeze²,

Salas³

2011

Ecological Modelling

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A new understanding of the consequences of how ecosystem elements are interconnected is emerging from the development and application of Ecological Network Analysis. The relative importance of indirect effects is central to this understanding, and the ratio of indirect flow to direct flow (I/D) is one indicator of their importance. Two methods have been proposed for calculating this indicator. The unit approach shows what would happen if each system member had a unit input or output, while the realized technique determines the ratio using the observed system inputs or outputs. When using the unit method, the input oriented and output oriented ratios can be different, potentially leading to conflicting results. However, we show that the input and output oriented I/D ratios are identical using the realized method when the system is at steady state. This work is a step in the maturation of Ecological Network Analysis that will let it be more readily testable empirically and ultimately more useful for environmental assessment and management.

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Section: Model Inputmentioning

confidence: 99%

“…Borrett and Freeze (2011) focused on the distinction between the idealized and realized forms of the I/D ratio. Here we focus on contrasting the input and output oriented analyses.…”

Section: Ecological Network Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Equivalence of the realized input and output oriented indirect effects metrics in Ecological Network Analysis

Borrett¹,

Freeze²,

Salas³

2011

Ecological Modelling

Self Cite

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Location and foraging as basis for classification of biotic interactions

Khabibullin

2016

Theory Biosci.

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Ecologists face an overwhelming diversity of ecological relationships in natural communities. In this paper, I propose to differentiate various types of the interspecific relations on the basis of two factors: relative localization and foraging activity of interacting partners. I advocate recognition of four types of environments: internal, surface, proximate external and distant external. Then I distinguish four types of synoikia-one partner lives in different degree of proximity to another; and four types of synmensalism: one partner forages in different degree of proximity to another. Intersection of localization-based (four subtypes of synoikia) and foraging-based (four subtypes of synmensalism) rows results in 16 types of interactions. This scheme can serve as a framework that manages diverse biotic interactions in a standardized way. I have made the first step to set up nomenclature standards for terms describing interspecific interactions and hope that this will facilitate research and communication.

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Throughflow centrality is a global indicator of the functional importance of species in ecosystems

Borrett

2013

Ecological Indicators

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To better understand and manage complex systems like ecosystems it is critical to know the relative contribution of the system components to the system function. Ecologists and social scientists have described a diversity of ways that individuals can be important; This paper makes two key contributions to this research area. First, it shows that throughflow (T j ), the total energy or matter entering or exiting a system component, is a global indicator of the relative contribution of the component to the whole system activity. Its global because it includes the direct and indirect exchanges among community members. Further, throughflow is a special case of Hubbell status or centrality as defined in social science. This recognition effectively joins the concepts, enabling ecologists to use and build on the broader centrality research in network science. Second, I characterize the distribution of throughflow in 45 empirically-based trophic ecosystem models. Consistent with theoretical expectations, this analysis shows that a small fraction of the system components are responsible for the majority of the system activity. In 73% of the ecosystem models, 20% or less of the nodes generate 80% or more of the total system throughflow. Four or fewer nodes are required to account for 50% of the total system activity and are thus defined as community dominants. 122 of the 130 dominant nodes in the 45 ecosystem models could be classified as primary producers, dead organic matter, or bacteria. Thus, throughflow centrality indicates the rank power of the ecosystems components and shows the concentration of power in the primary production and decomposition cycle. Although these results are specific to ecosystems, these techniques build on flow analysis based on economic input-output analysis. Therefore these results should be useful for ecosystem ecology, industrial ecology, the study of urban metabolism, as well as other domains using input-output analysis.

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Reconnecting environs to their environment

Cited by 14 publications

References 71 publications

Equivalence of the realized input and output oriented indirect effects metrics in Ecological Network Analysis

Equivalence of the realized input and output oriented indirect effects metrics in Ecological Network Analysis

Location and foraging as basis for classification of biotic interactions

Throughflow centrality is a global indicator of the functional importance of species in ecosystems

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