arXiv subjects

Ralf Schwamborn

Publications and source records attributed to Ralf Schwamborn.

4 recordsLinked to original sources

arXiv2026

Is normalized biomass really abundance? pitfalls, artifacts, and misconceptions in the field of size spectra analysis: a case for back-transformed spectra and standardized binning

The NBSS (normalized biomass size spectrum) is a common, intuitive approach for the study of natural ecosystems. However, very few studies have been dedicated to verifying possible flaws and paradoxes in this widely used method. Evident points of concern of the NBSS method are 1.) the loss of variability due to binning and 2.) the use of intriguing non-biomass units (i.e. abundance units). The main objectives of this study were to verify, test and analyze the procedures involved in transformations that lead to the NBSS plot, and to check for the correctness of currently used units, while testing the hypothesis that NBSS indeed represents biomass density, not abundance, while developing i.) a new conceptual framework, ii.) a new terminology within Size-spectrum Inference, Scaling, and Estimation (SIZE) theory, iii.) a novel back-transformation method, iv.) high-resolution kernel density estimation (KDE) plots of the density function shape, and v.) a new calculation method for numerical values, dimensions, and units. Extensive tests with in situ and synthetic (simulated) data were used to compare the original biomass distributions with binned outputs. Original biomass units (g m-3) and dimensions are retained in the proposed robust, bootstrapped backtransformed and normalized biomass spectrum (bNBS). Previously published common NBSS may be simply converted to quantitative biomass B by multiplying with a reference unity bin with (wR = 1 mass or volume unit). If a standardized framework (standard mass and space units, standard reference bin width wR) is used, the proposed bNBS may allow for a new approach of robust size spectra science, that allows for quantitative inter-comparisons of abundance and biomass across size ranges, regions, and time periods.

q-bio.QM↗

arXiv2026

Towards a compleat theory of ecosystem size spectra

The regularity of ecosystem size spectra is one of the most intriguing and relevant phenomena on our planet. Pelagic size spectra generally show a log-linearly downtrending shape, following a power-law distribution. A constant log-linear slope has been reported for many marine pelagic ecosystems, often being approximately b = -1. Conversely, there are variable trophic-level-biomass relationships (trophic pyramids). The contrasting observations of a constant size spectrum and highly variable trophic pyramids may be defined as the constant size spectrum - variable trophic dynamics paradox. Here, a mass-specific predator-prey-efficiency theory of size spectra (PETS) is presented and discussed. A thorough analysis of available data, literature, and models formed the basis for the PETS theoretical framework, where pelagic marine ecosystems are controlled by complex trophic processes such as resource-limitation stress and top-down regulation, thus establishing a discrete maximum carrying capacity spectrum. PETS consists of a series of equations and proposed stabilizing mechanisms. The slope b of the biomass-body mass spectrum can be predicted from predator-prey mass ratio (PPMR) and mass-specific trophic efficiency E (E = dlog10(B) / dTL), such that b = E / log10(PPMR) = -1. The proposed size-specific trophic equilibrium mechanisms stabilize the size spectrum, but not the trophic level - biomass relationship. The complete size spectrum obtained in situ (including living organisms and non-living particles) is discussed. This paper is intended as a plea for the integration of modeling approaches, to understand and integrate data and processes across communities including bacteria, plankton, fish and mammals, considering the effects of non-organismic particles.

q-bio.PE↗

arXiv2020

Growth and mortality of endangered land crabs (Cardisoma guanhumi) assessed through tagging with PITs and novel bootstrapped methods

The land crab Cardisoma guanhumi Latreille, 1828 is harvested in several countries in Latin America, and a critically endangered species. This is the first study to conduct bootstrapped tagging analysis (BTA) together with bootstrapped length-frequency analyses (BLFA). Crabs were sampled monthly in a mangrove patch at Itamaraca Island (Brazil), over 12 months, and marked with PIT tags. Both methods (BTA and BLFA) indicate very slow growth and Linf far above Lmax. BTA estimates were K = 0.12 y-1 (95% CI: 0.024 to 0.26 y-1), Linf = 118 mm (95% CI: 81 to 363 mm), Phi' = 1.23 log10(cm y-1) (95% CI: 0.86 to 1.36 log10(cm y-1)). Seasonality in growth was significant (p = 0.006, 95% CI for C: 0.15 to 0.93, median: C = 0.56). Pairs of K and Linf always followed narrow Phi' isopleths. Total mortality was Z = 2.18 y-1 (95% CI = 1.7 to 4.5 y-1). Slow growth and a very high Z/K ratio highlight the need for protective measures. BTA results were 2.2 to 3 times more precise than BLFA. Traditional length-based methods produced grossly biased results, indicating the urgent need for new, robust approaches and a critical reevaluation of long-standing methods and paradigms.

q-bio.QM↗

arXiv2018

How reliable are the Powell-Wetherall plot method and the maximum-length approach? Implications for length-based studies of growth and mortality

Length-based methods are the cornerstone of many population studies and stock assessments. This study tested two widely used methods: the Powell-Wetherall (P-W) plot and the Lmax approach, i.e., estimating Linf directly from Lmax. In most simulations, P-W estimates of the ratio total mortality / growth (Z/K ratio) were biased beyond acceptable limits (bias > 30%). Bias in Z/K showed a complex behavior, without possible corrections. Estimates of asymptotic length (Linf) were less biased than Z/K, but were very sensible to intra-cohort variability in growth and to changes in the occurrence of large individuals in the sample. Exclusion of the largest size classes during the regression procedure or weighing by abundance does not solve these issues. Perfect linearization of the data and absurdly narrow confidence intervals for Z/K will lead users to erroneous overconfidence in outputs. Clearly, the P-W method is not suitable for the assessment of Z/K ratios of natural populations. Estimation of Linf may be tentatively possible under very specific conditions, with necessary external verifications. Also, this study demonstrates that there is no way to estimate Linf directly from Lmax, since there is no particular relationship to expect a priori between Linf and Lmax. Errors in estimating Linf directly affect the estimate of the growth constant K and all other subsequent calculations in population studies, stock assessments and ecosystem models. New approaches are urgently needed for length-based studies of body growth (e.g., unconstrained curve fit with subsequent bootstrapping), that consider the inherent uncertainty regarding the underlying data and processes.

q-bio.PE↗