Response to comments on “Uncertainty principle in niche assessment: A solution to the dilemma redundancy vs. competitive exclusion, and some analytical consequences”
Introduction
Rodríguez et al. (2015a), starting from large sequences of statistical frequency distributions of species diversity values, have shown that in the same measure in which the spectrum of species diversity per plot (Hp: diversity index of Shannon at the plot level; see Rodríguez et al., 2015a; Eq. (1)) in which species live is assessed with higher accuracy (lower standard deviation: σ) there is an increment of σ in the measurement of the spectrum of eco-kinetic energy values per plot (Eep: a proxy for trophic energy; additional explanations in Section 2), and vice versa. So there is an insurmountable level of inaccuracy in our description of the ecological niche. Rodríguez et al. (2015a) named this trade-off as quantum ecological uncertainty (QEU, hereafter; additional explanations in Section 2). Under these circumstances, it is impossible to increase the accuracy of our knowledge about the nature and intensity of competition as much as we want by means of conventional methods. So, it is necessary to apply a wave-like interpretation of ecosystem functioning; an option that has also been proposed by the very authors that have proposed the QEU (see Rodríguez et al., 2015b). Thus, a debate that has endured for decades (see Lewin, 1983), has arrived to a win-win solution: species coexistence is possible only because when the hypothesis of functional redundancy (HFR) is true in one dimension (either low values of σHp or σEep) the competitive exclusion principle (CEP) is influencing in the opposite one (either high values of σEep or σHp), and vice versa. After all ecologists, willy nilly, have been forced to accept the coexistence of CEP and HRF in the collective academic mind, perhaps as an unwitting reflection that species coexistence depends on a combination of both alternatives in the real world.
The main goal of this article is to perform a comparative analysis in order to elucidate in what a measure the proposal of the authors of QEU, or the proposal of their critics (Kalmykov and Kalmykov, 2016), matches with the traits of any scientific model defined as an incomplete reflection of reality whose main goal, instead of reaching a “universal truth”, is obtaining good testable hypotheses relevant to understand important problems (see Levins, 1966, p. 430) in practice. The general fulfillment of QEU is additionally supported in this article by a very condensed inclusion (Appendix A, and a few lines at the end of the first paragraph in Section 3) of additional results from field data, surveyed under different circumstances in comparison with previous data, from two inland water taxocenes (rotifers and crustaceans, Acton Lake, Ohio, U.S.A.) to which this model has not been applied so far.
Section snippets
Epistemological inaccuracies in the criticism from Kalmykov and Kalmykov (2016)
Kalmykov and Kalmykov (2016, p. 1) start with a rhetorical resource or “argumentum ad verecundiam” (appeal to authority) that pervades their article as a whole: “I can never satisfy myself until I can make a mechanical model of a thing. If I can make a mechanical model, I can understand it. As long as I cannot make a mechanical model all the way through I cannot understand” (Lord Kelvin). A preliminary conceptual clarification is necessary here: What is the most probable meaning of the term
Fragmentary understanding about the principles that support QEU, and incomplete review of the literature that sustains the proposal criticized by Kalmykov and Kalmykov (2016)
The “gedankenexperiment” proposed by Kalmykov and Kalmykov (2016, p. 3) to refute QEU is unrealistically restrictive due to several reasons: (a) A beetle that is in hibernation is transiently “offline” from its ecological network, so it has no “ecological behavior” at all because its participation in the flow of energy tends to 0. (b) “One person as an observer vs. one beetle as a target of observation” is an observation without the statistical nature of any scientific observation in ecology or
References (16)
- et al.
On ecological modelling problems in the context of resolving the biodiversity paradox
Ecol. Modell.
(2016) - et al.
Ecological state equation
Ecol. Modell.
(2012) - et al.
Biomass-dispersal trade-off and the functional meaning of species diversity
Ecol. Modell.
(2013) - et al.
Uncertainty principle in niche assessment: a solution to the dilemma redundancy vs. competitive exclusion, and some analytical consequences
Ecol. Modell.
(2015) - et al.
Distribution of species diversity values: a link between classical and quantum mechanics in ecology
Ecol. Modell.
(2015) - et al.
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
Ecol. Modell.
(2007) Science and Information Theory
(1962)Thermodynamics and an Introduction to Thermostatistics
(1985)