Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 1201.5211

Phytoplankton competition in deep biomass maximum

Alexei B. Ryabov
View original source ↗Read source document ↗Export metadata ↓

Abstract

Resource competition in heterogeneous environments is still an unresolved problem of theoretical ecology. In this article I analyze competition between two phytoplankton species in a deep water column, where the distributions of main resources (light and a limiting nutrient) have opposing gradients and co-limitation by both resources causes a deep biomass maximum. Assuming that the species have a trade-off in resource requirements and the water column is weakly mixed, I apply the invasion threshold analysis (Ryabov and Blasius 2011) to determine relations between environmental conditions and phytoplankton composition. Although species deplete resources in the interior of the water column, the resource levels at the bottom and surface remain high. As a result, the slope of resources gradients becomes a new crucial factor which, rather than the local resource values, determines the outcome of competition. The value of resource gradients nonlinearly depend on the density of consumers. This leads to complex relationships between environmental parameters and species composition. In particular, it is shown that an increase of both the incident light intensity or bottom nutrient concentrations favors the best light competitors, while an increase of the turbulent mixing or background turbidity favors the best nutrient competitors. These results might be important for prediction of species composition in deep ocean.

Explore related subjects

q-bio.PEnlin.AOnlin.PS

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Alexei B. Ryabov. 2012-01-25. Phytoplankton competition in deep biomass maximum. https://doi.org/10.1007/s12080-012-0158-0

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

From daylight to darkness: a nonlocal model of circadian activity cycles

An animal's ability to perceive its surroundings, as well as the ecological interactions it experiences, can be strongly influenced by the sleep patterns of both itself and surrounding species. Animals with limited sensory capabilities may struggle to navigate their habitat at night, while in a predator-prey system, it may be detrimental for prey to be inactive while predators are awake and hunting. Here, we develop a general mathematical framework to study these interactions using partial differential equations, incorporating activity cycles and daylight-dependent perception into existing models of animal movement. We show that both the dominant sensory mode and the length of daylight are key factors determining the strength of aggregation in social species. Extending this framework to a two-species predator-prey system, we use game-theoretic approaches to show that the equilibrium sleep strategy of each species is shaped not only by its own sensory capabilities, but also by those of its ecological opponent. Depending on the sensory capabilities of the two species, equilibrium strategies may consist of a single sleep pattern or a combination of multiple sleep patterns.

q-bio.PE↗
arXiv2026

Evolution as fitness landscape navigation: concepts, measures, and emerging questions

Fitness landscapes are mappings between genotypes, phenotypes, and fitness that shape evolution. In recent years, empirical work and theoretical models have greatly advanced our understanding of how populations navigate rugged fitness landscapes. Here, we provide a timely review of the theoretical aspects of this field. Its rapidly growing literature employs a wide range of terms, which are sometimes used ambiguously or inconsistently. We therefore begin by defining the major concepts and the field's vocabulary, highlighting our own terminology choices wherever needed. We then review key results on the relationships between epistasis, ruggedness, accessibility, and navigability for genotype-fitness maps, highlighting several complex and sometimes counterintuitive connections that have emerged. Further, we review how the conserved structural properties of the underlying genotype-phenotype map, which can lead to the formation of large connected neutral networks of genotypes, influence dynamics on fitness landscapes. We then compare the two levels to study landscape navigation: the level of genotype-phenotype maps and the level of genotype-fitness maps. Our review leads us to propose a new measure of navigability, based on evolutionary outcomes, that is broadly applicable and overcomes limitations of existing measures. Finally, we highlight examples from the smaller body of work that relaxes the common assumption of fitness-monotonic paths on static landscapes, and discuss how this can fundamentally change the nature of fitness landscape navigation. Throughout the review, we identify directions for future work to fill existing gaps and to synthesize the disparate strands of research within the field.

q-bio.PE↗
arXiv2026

Best Matches in Phylogenetic Networks

Best match graphs (BMGs) were introduced in mathematical phylogenetics to describe the concept of closest relatives for related genes (leaves of rooted tree) in different organisms (defining leaf colors). We generalize this concept here to leaf-colored rooted networks, where least common ancestors are in general neither unique nor comparable. We characterize BMGs of rooted networks as those vertex-colored digraphs that are properly colored and satisfy an easy-to-check condition that we call the sicor-in-hub property. BMGs can be recognized in linear time and an explaining network can be constructed in quadratic time. Analogous results are obtained for reciprocal best match graphs (RBMGs), where an edge $\{x,y\}$ corresponds to pairs of vertices with different color that are mutually closest relatives.

q-bio.PE↗