Role Of Spatial Structure Research Articles

The role of spatial structure in multi-deme models of evolutionary rescue.

Genetic variation and population sizes are critical factors for successful adaptation to novel environmental conditions. Gene flow between sub-populations is a potent mechanism to provide such variation and can hence facilitate adaptation, for instance by increasing genetic variation or via the introduction of beneficial variants. On the other hand, if gene flow between different habitats is too strong, locally beneficial alleles may not be able to establish permanently. In the context of evolutionary rescue, intermediate levels of gene flow are therefore often optimal for maximizing a species chance for survival in metapopulations without spatial structure. To which extent and under which conditions gene flow facilitates or hinders evolutionary rescue in spatially structured populations remains unresolved. We address this question by studying the differences between evolutionary rescue in the island model and in the stepping stone model in a gradually deteriorating habitat. We show that evolutionary rescue is modulated by the rate of gene flow between different habitats, which in turn depends strongly on the spatial structure and the pattern of environmental deterioration. We use these insights to show that in many cases spatially structured models can be translated into a simpler island model using an appropriately scaled effective migration rate.

Spatial-temporal modeling of initial COVID-19 diffusion: The cases of the Chinese Mainland and Conterminous United States

ABSTRACT COVID-19 outbreaks in China in late December 2019, then in the United States (US) in early 2020. In the initial wave of diffusion, the virus respectively took 14 and 33 days to spread across the provinces/states in the Chinese mainland and the coterminous US, during which there are 43% and 70% zero entries in the space-time series for China and US respectively, indicating a zero-inflated count process. A logistic growth curve as a function of the number of days since the first case appeared in each of these countries accurately portrays the national aggregate per capita rates of infection for both. This paper presents two space-time model specifications, one based upon the generalized linear mixed model, and the other upon Moran eigenvector space-time filtering, to describe the spread of COVID-19 in the initial 19 and 58 days across the Chinese mainland and the coterminous US, respectively. Results from these case studies show both models shed new light on the role of spatial structures in COVID-19 diffusion, models that can forecast new cases in subsequent days. A principal finding is that describing the spatio-temporal diffusion of COVID-19 benefits from including a hierarchical structural component to supplement the commonly employed contagion component.

A non-linear effect of the spatial structure of the soil ectomycorrhizal spore bank on the performance of pine seedlings.

The spatial structure of the environment is known to affect ecological processes. Unlike the spatial structure of negative interactions, such as competition and predation, the role of spatial structure in positive interaction has received less attention. We tested how the spatial structure of spores of ectomycorrhizal fungi (EMF) in the soil affects the growth of Aleppo pine (Pinus halepensis) seedlings. Spores were spatially distributed at four different levels of patchiness (1 patch, 4 patches, 8 patches and complete mixing) in 4 L pots (all pots received the same total amount of spores). Based on previous findings, we hypothesized that plant performance would gradually increase from the single patch treatment to the complete mixing. However, we found a non-linear response to patchiness. Specifically, plants were largest in the single patch and complete mixing while those in the 4 and 8 patch treatments were the smallest. This non-monotonic response, which might be the result of spatially determined colonization timing or community composition, suggests that the spatial structure of EMF spores has a complex effect on seedling growth.

The spatial structure debate in spatial interaction modeling: 50 years on

Spatial interaction and spatial structure are foundational geographical abstractions, though there is often variation in how they are conceptualized and deployed in quantitative models. In particular, the last five decades have produced an exceptional diversity regarding the role of spatial structure within spatial interaction models. This is explored by outlining the initiation and development of the notion of spatial structure within spatial interaction modeling and critically reviewing four methodological approaches that emerged from ongoing debate about the topic. The outcome is a comprehensive coverage of the past and a sketch of one potential path forward for advancing this long-standing inquiry.

Dispersal traits as benthic invertebrate assemblage drivers in a neotropical large river

Metacommunity theory is a mechanistic framework that explains the interdependence of local factors and regional processes as community drivers. Recent evidence suggests that dispersal mode is a key trait that potentially affects metacommunity dynamics. We analyzed the distribution patterns of benthic macroinvertebrates with different dispersal modes in the Middle Paraná, a neotropical large river. We assessed the relative importance of local environmental conditions and regional spatial structure as assemblage drivers. Aquatic and aerial dispersers presented Clementsian and Gleasonian structures, respectively. For both groups, local environmental conditions influenced community assembly, and spatial structure (overland distances) also affected the distribution of aerial dispersers. Our study highlights that the role of spatial structure as a driver of benthic metacommunities depends on species' dispersal modes. Aerial dispersers responded to regional spatial variables and it is likely that these organisms are also influenced by mass effects. Our results are consistent with current ideas of metacommunity dynamics in large rivers, where dispersal is not considered to limit the distribution of benthic organisms.

The role of spatial structure in the collapse of regional metapopulations.

Many wildlife populations are either naturally, or as a result of human land use, patchily distributed in space. The degree of fragmentation-specifically the remaining patch sizes and habitat configuration-is an important part of population dynamics. Demographic stochasticity is also likely to play an important role in patchy habitats that host small local populations. We develop a simulation model to evaluate the significance of demographic stochasticity and the role fragmentation plays in the determination of population dynamics and the risk of extinction of populations on habitat patches. Our model is formulated as a Markov-chain stochastic process on a finite, spatially explicit array of patches in which probability of successful dispersal is a function of interpatch distance. Unlike past work, we explicitly model local population dynamics and examine how these scale up to the entire population. As a test case, we apply the model to the American pika (Ochotona princeps) population living on the ore dumps in the ghost mining town of Bodie, California. This population has been studied nearly continuously for over four decades and has been of conservation concern as the southern half of the population declined precipitously beginning in 1989. Our model suggests that both the specific configuration of habitat and landscape heterogeneity are necessary and sufficient predictors of the eventual extinction of the southern constellation of patches. This example has important implications, as it suggests that fragmentation alone can lead to regional extinctions within metapopulations.

Unifying population and landscape ecology with spatial capture–recapture

Spatial heterogeneity in the environment induces variation in population demographic rates and dispersal patterns, which result in spatio‐temporal variation in density and gene flow. Unfortunately, applying theory to learn about the role of spatial structure on populations has been hindered by the lack of mechanistic spatial models and inability to make precise observations of population state and structure. Spatial capture–recapture (SCR) represents an individual‐based analytic framework for overcoming this fundamental obstacle that has limited the utility of ecological theory. SCR methods make explicit use of spatial encounter information on individuals in order to model density and other spatial aspects of animal population structure, and they have been widely adopted in the last decade. We review the historical context and emerging developments in SCR models that enable the integration of explicit ecological hypotheses about landscape connectivity, movement, resource selection, and spatial variation in density, directly with individual encounter history data obtained by new technologies (e.g. camera trapping, non‐invasive DNA sampling). We describe ways in which SCR methods stand to advance the study of animal population ecology.

Selection against somatic parasitism can maintain allorecognition in fungi

Fusion between multicellular individuals is possible in many organisms with modular, indeterminate growth, such as marine invertebrates and fungi. Although fusion may provide various benefits, fusion usually is restricted to close relatives by allorecognition, also called heterokaryon or somatic incompatibility in fungi. A possible selective explanation for allorecognition is protection against somatic parasites. Such mutants contribute less to colony functions but more to reproduction. However, previous models testing this idea have failed to explain the high diversity of allorecognition alleles in nature. These models did not, however, consider the possible role of spatial structure. We model the joint evolution of allorecognition and somatic parasitism in a multicellular organism resembling an asexual ascomycete fungus in a spatially explicit simulation. In a 1000-by-1000 grid, neighbouring individuals can fuse, but only if they have the same allotype. Fusion with a parasitic individual decreases the total reproductive output of the fused individuals, but the parasite compensates for this individual-level fitness reduction by a disproportional share of the offspring. Allorecognition prevents the invasion of somatic parasites, and vice versa, mutation towards somatic parasitism provides the selective conditions for extensive allorecognition diversity. On the one hand, if allorecognition diversity did not build up fast enough, somatic parasites went to fixation; conversely, once parasites had gone to fixation no allorecognition diversity built up. On the other hand, the mere threat of parasitism could select for high allorecognition diversity, preventing invasion of somatic parasites. Moderate population viscosity combined with weak global dispersal was optimal for the joint evolution of allorecognition and protection against parasitism. Our results are consistent with the widespread occurrence of allorecognition in fungi and the low degree of somatic parasitism. We discuss the implications of our results for allorecognition in other organism groups.

Evolution of microbial markets.

Biological market theory has been used successfully to explain cooperative behavior in many animal species. Microbes also engage in cooperative behaviors, both with hosts and other microbes, that can be described in economic terms. However, a market approach is not traditionally used to analyze these interactions. Here, we extend the biological market framework to ask whether this theory is of use to evolutionary biologists studying microbes. We consider six economic strategies used by microbes to optimize their success in markets. We argue that an economic market framework is a useful tool to generate specific and interesting predictions about microbial interactions, including the evolution of partner discrimination, hoarding strategies, specialized versus diversified mutualistic services, and the role of spatial structures, such as flocks and consortia. There is untapped potential for studying the evolutionary dynamics of microbial systems. Market theory can help structure this potential by characterizing strategic investment of microbes across a diversity of conditions.

Spatial–Semantic Display Processing: The Role of Spatial Structure on Recall

The purpose of the present study was to test a model of spatial–semantic display processing by comparing the aided and unaided recall of information presented in a node-link format (knowledge map) to the aided and unaided recall of information presented in a text format. Structural icons of the knowledge map and text with the verbiage removed were used to aid retrieval in some conditions. Participants were randomly assigned to one of eight groups formed by the complete crossing of three factors: knowledge map versus text, structural icon at recall versus no structural icon at recall, and immediate versus delayed recall. Knowledge map groups outperformed text groups on essay tests and they more accurately remembered where information was located within the materials. Both knowledge map and text icon-aided recall groups had significantly better performance than the no icon, unaided recall groups (particularly on main ideas).

Modeling of self-excited wake oscillations by amplitude equations

The purpose of this overview is to show the utility of simple amplitude equations for the modeling of various vortex-shedding phenomena in bluff-body (cylinder) wakes. After a review of global modes that leads to the physical concept of local self-excited oscillators acting as “generators” of Kármán vortices in the near wake, the characterization of the vortex street by a single Stuart-Landau oscillator is discussed. The success beyond expectation of this model as well as the problems associated with it are documented. Among them, we focus on the neglect of spatial structure in the simple temporal Stuart-Landau model. The role of spatial structure in the streamwise direction is highlighted by a short discussion of the effect of feedback control, while in the last part of the paper the model is extended to include the spanwise structure of vortex shedding, in particular the effect of the cylinder ends.