Indirect effects and distributed control in ecosystems: Distributed control in the environ networks of a seven-compartment model of nitrogen flow in the Neuse River Estuary, USA-Time series analysis

dc.contributor.author	Schramski, JR	en
dc.contributor.author	Gattie, DK	en
dc.contributor.author	Patten, BC	en
dc.contributor.author	Borrett, SR	en
dc.contributor.author	Fath, BD	en
dc.contributor.author	Whipple, SJ	en
dc.date.accessioned	2014-06-06T06:47:24Z
dc.date.available	2014-06-06T06:47:24Z
dc.date.issued	2007	en
dc.identifier.issn	03043800	en
dc.identifier.uri	http://dx.doi.org/10.1016/j.ecolmodel.2007.03.023	en
dc.identifier.uri	http://62.217.125.90/xmlui/handle/123456789/3576
dc.subject	Distributed control	en
dc.subject	Environs	en
dc.subject	Network environ analysis	en
dc.subject	Neuse River Estuary	en
dc.subject	Nitrogen cycling	en
dc.subject.other	Distributed parameter control systems	en
dc.subject.other	Environmental impact	en
dc.subject.other	Mathematical models	en
dc.subject.other	Nitrogen	en
dc.subject.other	Sediments	en
dc.subject.other	Boundary inflow	en
dc.subject.other	Ecological control	en
dc.subject.other	Linear compartmental systems	en
dc.subject.other	Short-term responses	en
dc.subject.other	Steady-state models	en
dc.subject.other	Ecosystems	en
dc.subject.other	compartmentalization	en
dc.subject.other	ecosystem modeling	en
dc.subject.other	estuarine ecosystem	en
dc.subject.other	network analysis	en
dc.subject.other	nitrogen cycle	en
dc.subject.other	steady-state equilibrium	en
dc.subject.other	systems analysis	en
dc.subject.other	time series analysis	en
dc.subject.other	Neuse Estuary	en
dc.subject.other	North America	en
dc.subject.other	North Carolina	en
dc.subject.other	United States	en
dc.title	Indirect effects and distributed control in ecosystems: Distributed control in the environ networks of a seven-compartment model of nitrogen flow in the Neuse River Estuary, USA-Time series analysis	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.ecolmodel.2007.03.023	en
heal.publicationDate	2007	en
heal.abstract	The methods of network environ analysis (NEA) currently apply to steady-state models. Networks of real ecosystems are near steady-state in long-term mean characteristics, but are dynamic in short-term responses. A formal mathematical approach to dynamic NEA analysis has never been fully developed, though Hippe [Hippe, P.W., 1983. Environ analysis of linear compartmental systems: the dynamic, time-invariant case. Ecol. Model. 19, 1-26] offers one approach. Another potential approach to addressing this limitation is to analyze a discrete-time series of steady-state models, each a snapshot for the time period it represents. Using concepts from open-loop control theory, four throughflow-based ecological control terms (control ratio, CR; control difference, CD; system control, scj; and total system control, TC) as developed using an environ framework are evaluated for 16 consecutive seasons of nitrogen cycling in the Neuse River Estuary, North Carolina, USA. Results of this assessment offer a quantitative measure of the quasi-dynamic distributed control in this network. The NOx and Sediment components assume opposing but dominant roles (high scj magnitudes) in all 16 seasons. Low total compartmental throughflow (Ti) to respective boundary inflow (zi) or outflow (yj) ratios are shown to be indicators of component control dominance, suggesting a role for boundary flows in the consideration of a system component's dominance. This conclusion may also be a property of the high cycling nature of this nitrogen model (average Finn cycling index of 89% for all 16 seasons). TC appears to be correlated with total system throughflow (TST), suggesting that TST may indicate a system's distributed control patterns. This correlation may likewise be fruitful if TST proves to be an indicator for system stability, an important and logical consideration in the notion of control. © 2007 Elsevier B.V. All rights reserved.	en
heal.journalName	Ecological Modelling	en
dc.identifier.issue	1-2	en
dc.identifier.volume	206	en
dc.identifier.doi	10.1016/j.ecolmodel.2007.03.023	en
dc.identifier.spage	18	en
dc.identifier.epage	30	en