Body size, energy consumption and allometric scaling: a new dimension in the diversity?stability debate

Abstract

A new theoretical approach is developed that links the allometry of energy partitioning among differently-sized organisms in ecological community to community stability. The magnitude of fluctuations of plant biomass introduced by plant-feeding heterotrophs is shown to grow rapidly with increasing body size. To keep these fluctuations at a low level compatible with ecosystem stability, the share of ecosystem primary productivity claimed by plant-feeding heterotrophs should decrease with increasing body size. In unstable environments the ecological restrictions on biotic fluctuations are lessened and net primary productivity can be distributed more evenly among differently sized organisms. Within the developed approach it is possible to quantitatively estimate not only the scaling exponents in the dependence of population density and biomass of heterotrophs on body size, but also the absolute values of energy fluxes claimed by organisms of a given size in stable communities. Theoretical predictions are tested against diverse sets of empirical data. It is shown that in stable ecological communities the largest heterotrophs are allowed to consume no more than several tenths of percent of net primary productivity.

On the use of biomass size spectra linear adjustments to design ecosystem indicators

“…On the other hand, flatter size distributions can reduce the total biomass of the community when the value of b crosses the -1.0 threshold, becoming less negative and eventually transforming the size distribution into an inverted biomass pyramid with a consequently lower level of stability (Makarieva et al 2004). Our simulations also show that when the producers in the system maintain constant carrying capacity, increases in a of the NBSS take place while b decreases, even when community biomass remains constant.…”

“…(ii) Communities with b>-1: these represent flatter biomass pyramids, which according to Makarieva et al (2004) are more unstable than steeper biomass pyramids. They also displayed a strong correlation between b and a parameters ( Fig.…”

Mean mass-specific metabolic rates are strikingly similar across life's major domains: Evidence for life's metabolic optimum

“…From this perspective, it is noteworthy that life's most important energy flux-primary productivity-is ensured by living beings that, in the basal state, all function near the optimal metabolic rate, be they blue-green algae, eukaryotic phytoplankton, macroalgae, or trees ( Table 1). The most important consumers of this flux, prokaryotes, which can consume up to 95% of primary productivity in stable ecosystems (42), are also characterized by this optimal rate. The most abundant invertebrates on land (insects) and in the ocean [copepods (11)], which claim the second largest share of the biosphere's energy flux after the unicells (42), metabolize at the optimal rate also.…”

“…The most important consumers of this flux, prokaryotes, which can consume up to 95% of primary productivity in stable ecosystems (42), are also characterized by this optimal rate. The most abundant invertebrates on land (insects) and in the ocean [copepods (11)], which claim the second largest share of the biosphere's energy flux after the unicells (42), metabolize at the optimal rate also. Thus, at physiological rest the biosphere appears to run on average predominantly at the optimal rate.…”

Expanding ecological appropriation approach: Solar space method and a case study in Yangzhou city, East China

“…(3) EF is just a static analysis of stock, and lacks dynamic analysis of fluxes, so it cannot reflect the process of ecosystems appropriation in a period of time (Moffatt, 2000;Lenzen and Murray, 2001). (4) The inaccurateness in calculation: it excessively simplified the relationships between nature and humans, and ignored their complex dynamic behaviors such as multi-scale hierarchy, resilience, non-linearity, discontinuity and uncertainty, etc., which universally occurs in EF calculations (Anand and Li, 2001;Li et al, 2004;Makarieva et al, 2004Makarieva et al, , 2005Makarieva et al, , 2006Makarieva et al, , 2008aMakarieva et al, , 2008b. Therefore, it has very low predictability (Moffatt, 2000;Rees, 2000).…”